[ { "key": "2F2M4SHI", "version": 440, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/2F2M4SHI", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/2F2M4SHI", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Molenberghs et al.", "parsedDate": "2004", "numChildren": 0 }, "data": { "key": "2F2M4SHI", "version": 440, "itemType": "journalArticle", "title": "A perspective on surrogate endpoints in controlled clinical trials", "creators": [ { "creatorType": "author", "firstName": "Geert", "lastName": "Molenberghs" }, { "creatorType": "author", "firstName": "Tomasz", "lastName": "Burzykowski" }, { "creatorType": "author", "firstName": "Ariel", "lastName": "Alonso" }, { "creatorType": "author", "firstName": "Marc", "lastName": "Buyse" } ], "abstractNote": "The last couple of decades have seen a large amount of activity in the area of surrogate marker and surrogate endpoint validation, both from a clinical and a statistical perspective. Prentice1 made a pivotal contribution in the context of a single trial. Subsequently, the framework he proposed has been discussed, criticized, and extended. An important class of extensions considers several rather than a single trial. Recently, a lot of work has been done in this so-called hierarchical or meta-analytic framework. In this paper, we review both the single trial and the hierarchical framework. A number of applications, scattered throughout the literature, are brought together. We outline the statistical issues involved in trying to validate surrogate endpoints. Clearly statistical evidence should only be seen as a component in a decision making process that also involves a number of clinical and biological considerations.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Juin 1, 2004", "volume": "13", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "177-206", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1191/0962280204sm362ra", "citationKey": "Molenberghsperspectivesurrogate2004", "url": "http://smm.sagepub.com/cgi/content/abstract/13/3/177", "accessDate": "2009-03-29T14:05:55Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0038", "rights": "", "extra": "00052", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:38:11Z" } }, { "key": "2X6JZ5A4", "version": 440, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/2X6JZ5A4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/2X6JZ5A4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Gathmann et al.", "parsedDate": "2009-09", "numChildren": 0 }, "data": { "key": "2X6JZ5A4", "version": 440, "itemType": "journalArticle", "title": "The European internet-based patient and research database for primary immunodeficiencies: results 2006-2008", "creators": [ { "creatorType": "author", "firstName": "B", "lastName": "Gathmann" }, { "creatorType": "author", "firstName": "B", "lastName": "Grimbacher" }, { "creatorType": "author", "firstName": "J", "lastName": "Beauté" }, { "creatorType": "author", "firstName": "Y", "lastName": "Dudoit" }, { "creatorType": "author", "firstName": "N", "lastName": "Mahlaoui" }, { "creatorType": "author", "firstName": "A", "lastName": "Fischer" }, { "creatorType": "author", "firstName": "V", "lastName": "Knerr" }, { "creatorType": "author", "firstName": "G", "lastName": "Kindle" } ], "abstractNote": "Primary immunodeficiencies (PID) are rare diseases; therefore transnational studies are essential to maximize the scientific outcome and to improve diagnosis and therapy. In order to estimate the prevalence of PID in Europe as well as to establish and evaluate harmonized guidelines for the diagnosis and treatment of PID, the European Society for Immunodeficiencies (ESID) has developed an internet-based database for clinical and research data on patients with PID. This database is a platform for epidemiological analyses as well as the development of new diagnostic and therapeutic strategies and the identification of novel disease-associated genes. Within 4 years, 7430 patients from 39 countries have been documented in the ESID database. Common variable immunodeficiency (CVID) represents the most common entity, with 1540 patients or 20.7% of all entries, followed by isolated immunoglobulin (Ig)G subclass deficiency (546 patients, 7.4%). Evaluations show that the average life expectancy for PID patients varies from 1 to 49 years (median), depending on the type of PID. The prevalence and incidence of PID remains a key question to be answered. As the registration progress is far from finished we can only calculate minimum values for PID, with e.g. France currently showing a minimum prevalence of 3.72 patients per 100,000 inhabitants. The most frequently documented permanent treatment is immunoglobulin replacement; 2819 patients (42% of all patients alive) currently receive this form of treatment.", "publicationTitle": "Clinical and Experimental Immunology", "publisher": "", "place": "", "date": "Sep 2009", "volume": "157 Suppl 1", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "3-11", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Clin. Exp. Immunol", "DOI": "10.1111/j.1365-2249.2009.03954.x", "citationKey": "GathmannEuropeaninternetbased2009", "url": "http://www.ncbi.nlm.nih.gov/pubmed/19630863", "accessDate": "2009-12-07T16:00:17Z", "PMID": "", "PMCID": "", "ISSN": "1365-2249", "archive": "", "archiveLocation": "", "shortTitle": "The European internet-based patient and research database for primary immunodeficiencies", "language": "", "libraryCatalog": "NCBI PubMed", "callNumber": "0040", "rights": "", "extra": "00088 PMID: 19630863", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-12-07T16:00:17Z", "dateModified": "2025-01-30T07:38:07Z" } }, { "key": "373XMHAS", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/373XMHAS", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/373XMHAS", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Roy", "parsedDate": "2007-10-01", "numChildren": 0 }, "data": { "key": "373XMHAS", "version": 439, "itemType": "journalArticle", "title": "Latent class models and their application to missing-data patterns in longitudinal studies", "creators": [ { "creatorType": "author", "firstName": "Jason", "lastName": "Roy" } ], "abstractNote": "Latent class models have been developed as a flexible way of modeling the correlation of multivariate data, as a method for discovering subpopulations with similar response profiles and as a dimension reduction tool. In this manuscript, we provide a review of some of this literature and describe specific developments in several statistical and substantive areas. We then describe latent class models that could be used for characterizing missing-data patterns in longitudinal studies with regularly spaced observation times, where there is a large amount of intermittent missing data. We illustrate by analyzing data from a longitudinal study of depression, where there were 379 unique missing-data patterns.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Octobre 1, 2007", "volume": "16", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "441-456", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/0962280206075311", "citationKey": "RoyLatentclass2007", "url": "http://smm.sagepub.com/cgi/content/abstract/16/5/441", "accessDate": "2009-03-29T14:05:47Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0002", "rights": "", "extra": "00007", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:38:02Z" } }, { "key": "7IDEF7TP", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/7IDEF7TP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/7IDEF7TP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Hanley and Dendukuri", "parsedDate": "2009", "numChildren": 0 }, "data": { "key": "7IDEF7TP", "version": 439, "itemType": "journalArticle", "title": "Efficient sampling approaches to address confounding in database studies", "creators": [ { "creatorType": "author", "firstName": "James A", "lastName": "Hanley" }, { "creatorType": "author", "firstName": "Nandini", "lastName": "Dendukuri" } ], "abstractNote": "Administrative and other population-based databases are widely used in pharmacoepidemiology to study the unintended effects of medications. They allow investigators to study large case series, and they document prescription medication exposure without having to contact individuals or medical charts, or rely on human recall. However, such databases often lack information on potentially important confounding variables. This review describes some of the sampling approaches and accompanying data-analysis methods that can be used to assess, and deal efficiently with, such confounding.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 2009", "volume": "18", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "81-105", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/0962280208096046", "citationKey": "HanleyEfficientsampling2009", "url": "http://smm.sagepub.com/cgi/content/abstract/18/1/81", "accessDate": "2009-03-29T14:53:45Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0003", "rights": "", "extra": "00005", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:38:00Z" } }, { "key": "8REK5975", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/8REK5975", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/8REK5975", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Formann and Kohlmann", "parsedDate": "1996", "numChildren": 0 }, "data": { "key": "8REK5975", "version": 439, "itemType": "journalArticle", "title": "Latent class analysis in medical research", "creators": [ { "creatorType": "author", "firstName": "Anton K", "lastName": "Formann" }, { "creatorType": "author", "firstName": "Thomas", "lastName": "Kohlmann" } ], "abstractNote": "In the introduction we give a brief characterization of the usual measures for indicating the quality of diagnostic procedures (sensitivity, specificity and predictive value) and we refer to their relationship to parameters of the latent class model. Different variants of latent class analysis (LCA) for dichotomous data are described in the following: the basic (unconstrained) model, models with parameters fixed to given values and with equality constraints on parameters, multigroup LCA including mixed-group vali dation, and linear logistic LCA including its relationship to the Rasch model and to the measurement of change in latent subgroups. The problem with the identifiability of latent class models and the possi bilities for statistically testing their fit are outlined. The second part refers to latent class models for polytomous data. Special attention is paid to simple variants having fixed and/or equated parameters and to log-linear extension of LCA with its possibility for including interactions on the latent level. Several examples are presented to illustrate typical applications of the model. The paper ends with some warnings that should be taken into consideration by potential users of LCA.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Juin 1, 1996", "volume": "5", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "179-211", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029600500205", "citationKey": "FormannLatentclass1996", "url": "http://smm.sagepub.com/cgi/content/abstract/5/2/179", "accessDate": "2009-03-29T14:08:09Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0067", "rights": "", "extra": "00090", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:58Z" } }, { "key": "9JRK56TB", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/9JRK56TB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/9JRK56TB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "McLachlan", "parsedDate": "1997", "numChildren": 0 }, "data": { "key": "9JRK56TB", "version": 439, "itemType": "journalArticle", "title": "On the EM algorithm for overdispersed count data", "creators": [ { "creatorType": "author", "firstName": "G J", "lastName": "McLachlan" } ], "abstractNote": "In this paper, we consider the use of the EM algorithm for the fitting of distributions by maximum likelihood to overdispersed count data. In the course of this, we also provide a review of various approaches that have been proposed for the analysis of such data. As the Poisson and binomial regression models, which are often adopted in the first instance for these analyses, are particular examples of a generalized linear model (GLM), the focus of the account is on the modifications and extensions to GLMs for the handling of overdispersed count data.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 1997", "volume": "6", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "76-98", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029700600106", "citationKey": "McLachlanEMalgorithm1997", "url": "http://smm.sagepub.com/cgi/content/abstract/6/1/76", "accessDate": "2009-03-29T14:57:02Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0016", "rights": "", "extra": "00025", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:56Z" } }, { "key": "AUZJ7XVV", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/AUZJ7XVV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/AUZJ7XVV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Bentler and Stein", "parsedDate": "1992", "numChildren": 0 }, "data": { "key": "AUZJ7XVV", "version": 439, "itemType": "journalArticle", "title": "Structural equation models in medical research", "creators": [ { "creatorType": "author", "firstName": "PM", "lastName": "Bentler" }, { "creatorType": "author", "firstName": "JA", "lastName": "Stein" } ], "abstractNote": "Structural equation modelling (SEM) is a modern statistical method that allows one to evaluate causal hypotheses on a set of intercorrelated nonexperimental data. The sample variances and covariances, and possibly the means, are compared to those predicted by a theory-based hypothetical model after optimal estimation of the parameters of the model. The goodness-of-fit of the empirical data to the hypothesized model is evaluated statistically. This review describes the underlying statistical theory and rationale of SEM. Both confirmatory factor analysis and latent variable path models are discussed. The applicability of SEM to assessment of reliability and validity is noted. A detailed example is provided, and several examples from the medical literature are briefly reviewed. Cautions regarding the possible misuse or misinterpretation of the technique are also mentioned. Possible future directions for the use of SEM in medical research are suggested. Two appendices provide more technical details.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Août 1, 1992", "volume": "1", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "159-181", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029200100203", "citationKey": "BentlerStructuralequation1992", "url": "http://smm.sagepub.com/cgi/content/abstract/1/2/159", "accessDate": "2009-03-29T14:02:21Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0108", "rights": "", "extra": "00146", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:55Z" } }, { "key": "BXZS75TE", "version": 439, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/BXZS75TE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/BXZS75TE", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Hedeker et al.", "parsedDate": "2000", "numChildren": 0 }, "data": { "key": "BXZS75TE", "version": 439, "itemType": "journalArticle", "title": "Random-effects regression analysis of correlated grouped-time survival data", "creators": [ { "creatorType": "author", "firstName": "Donald", "lastName": "Hedeker" }, { "creatorType": "author", "firstName": "Ohidul", "lastName": "Siddiqui" }, { "creatorType": "author", "firstName": "Frank B", "lastName": "Hu" } ], "abstractNote": "Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Avril 1, 2000", "volume": "9", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "161-179", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228020000900206", "citationKey": "HedekerRandomeffectsregression2000", "url": "http://smm.sagepub.com/cgi/content/abstract/9/2/161", "accessDate": "2009-03-29T14:53:26Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0057", "rights": "", "extra": "00083", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:50Z" } }, { "key": "C7RTIWFT", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/C7RTIWFT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/C7RTIWFT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Heath et al.", "parsedDate": "1998", "numChildren": 0 }, "data": { "key": "C7RTIWFT", "version": 438, "itemType": "journalArticle", "title": "Statistical methods in genetic research on smoking", "creators": [ { "creatorType": "author", "firstName": "Andrew C", "lastName": "Heath" }, { "creatorType": "author", "firstName": "Pamela AF", "lastName": "Madden" }, { "creatorType": "author", "firstName": "Nicholas G", "lastName": "Martin" } ], "abstractNote": "A growing body of evidence suggests that genetic factors have an important influence on the onset and course of smoking. Here we review some of the statistical methods that have been used to test for genetic influences on smoking behaviour, with a particular focus on studies of large national twin samples. We show how many of the hypotheses that have been tested using a genetic model-fitting approach have also been reformulated using logistic regression models that will be more familiar to epidemiologists. Such an approach is more easily extended to allow for sociocultural, as well as genetic, influences on smoking behaviour. Using either approach, data are consistent in indicating that certainly in men, and possibly in women, genetic factors play an important role in predicting which individuals who become cigarette smokers progress to being long-term persistent smokers.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Avril 1, 1998", "volume": "7", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "165-186", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029800700205", "citationKey": "HeathStatisticalmethods1998", "url": "http://smm.sagepub.com/cgi/content/abstract/7/2/165", "accessDate": "2009-03-29T14:56:59Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0046", "rights": "", "extra": "00050", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:48Z" } }, { "key": "D5MTKUX4", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/D5MTKUX4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/D5MTKUX4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Hopper", "parsedDate": "1993-11-01", "numChildren": 0 }, "data": { "key": "D5MTKUX4", "version": 438, "itemType": "journalArticle", "title": "Review papers : Variance components for statistical genetics: applications in medical research to characteristics related to human diseases and health", "creators": [ { "creatorType": "author", "firstName": "JL", "lastName": "Hopper" } ], "abstractNote": "RA Fisher introduced variance components in 1918. He synthesized Mendelian inheritance with Darwin's theory of evolution by showing that the genetic variance of a continuous trait could be decomposed into additive and non-additive components. The model can be extended to include environmental factors, interactions, covariation, and non-random mating. Identifiability depends critically on design. Methods of analysis include modelling the mean squares from a fixed effects analysis of variance, and covariance structure modelling, which can be extended to multivariate traits and has been used to study ordinal traits by reference to postulated, unmeasured, latent 'liabilities'. These methods operate on dependent observa tions within independent groups of the same size and structure, and therefore require balanced designs ('regular' pedigrees). A multivariate normal model handles data in its generic form, utilizes data efficiently from all members of pedigrees of unequal size or varying structure, accommodates individuals missing at random, and allows flexible modelling with tests of distributional assumptions and fit. Most analytical methods use least squares or maximum likelihood under normal theory. Robust methods, scale transforma tion, ascertainment, path diagrams and correlational path models (popular in behavioural genetics through addressing nonrandom mating and social interactions), 'heritability', and the contribution and limitations of statistical modelling to the 'nature-nurture' debate, are discussed.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Novembre 1, 1993", "volume": "2", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "199-223", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029300200302", "citationKey": "HopperReviewpapers1993", "url": "http://smm.sagepub.com/cgi/content/abstract/2/3/199", "accessDate": "2009-03-29T14:53:34Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Review papers", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0000", "rights": "", "extra": "00060", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:47Z" } }, { "key": "DWSFT36W", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/DWSFT36W", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/DWSFT36W", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Pickles and Crouchlev", "parsedDate": "1994-10-01", "numChildren": 0 }, "data": { "key": "DWSFT36W", "version": 438, "itemType": "journalArticle", "title": "Generalizations and applications of frailty models for survival and event data", "creators": [ { "creatorType": "author", "firstName": "Andrew", "lastName": "Pickles" }, { "creatorType": "author", "firstName": "Robert", "lastName": "Crouchlev" } ], "abstractNote": "A variety of survival models with both discrete and continuously distributed frailty is considered within a framework that involves the specification of three sub-models. An intensity sub-model specifies how the intensity is related to values of covariates and frailty; a measurement sub-model specifies how fallible measures of frailty are related to it; and an exposure sub-model specifies how frailty is distributed within the population. The models include those in which frailty is due to omitted covariates and those where it represents a covariate that has been measured subject to error. Multivariate frailty is also considered, with particular emphasis on models suitable for application to genetically related individuals, notably twins. A numerical example illustrates the use of a model with multivariate frailty for data on repeated exercise times.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Octobre 1, 1994", "volume": "3", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "263-278", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029400300305", "citationKey": "PicklesGeneralizationsapplications1994", "url": "http://smm.sagepub.com/cgi/content/abstract/3/3/263", "accessDate": "2009-03-29T14:08:26Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0036", "rights": "", "extra": "00039", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:45Z" } }, { "key": "E6DBET2H", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/E6DBET2H", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/E6DBET2H", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Xiaowei Yang et al.", "parsedDate": "2007", "numChildren": 0 }, "data": { "key": "E6DBET2H", "version": 438, "itemType": "journalArticle", "title": "Markov transition models for binary repeated measures with ignorable and nonignorable missing values", "creators": [ { "creatorType": "author", "firstName": "", "lastName": "Xiaowei Yang" }, { "creatorType": "author", "firstName": "Steven", "lastName": "Shoptaw" }, { "creatorType": "author", "firstName": "", "lastName": "Kun Nie" }, { "creatorType": "author", "firstName": "", "lastName": "Juanmei Liu" }, { "creatorType": "author", "firstName": "Thomas R.", "lastName": "Belin" } ], "abstractNote": "Motivated by problems encountered in studying treatments for drug dependence, where repeated binary outcomes arise from monitoring biomarkers for recent drug use, this article discusses a statistical strategy using Markov transition model for analyzing incomplete binary longitudinal data. When the mechanism giving rise to missing data can be assumed to be `ignorable', standard Markov transition models can be applied to observed data to draw likelihood-based inference on transition probabilities between outcome events. Illustration of this approach is provided using binary results from urine drug screening in a clinical trial of baclofen for cocaine dependence. When longitudinal data have `nonignorable' missingness mechanisms, random-effects Markov transition models can be used to model the joint distribution of the binary data matrix and the matrix of missingness indicators. Categorizing missingness patterns into those for occasional or `intermittent' missingness and those for monotonic missingness or `missingness due to dropout', the random-effects Markov transition model was applied to a data set containing repeated breath samples analyzed for expired carbon monoxide levels among opioid-dependent, methadone-maintained cigarette smokers in a smoking cessation trial. Markov transition models provide a novel reconceptualization of treatment outcomes, offering both intuitive statistical values and relevant clinical insights.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Août 1, 2007", "volume": "16", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "347-364", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/0962280206071843", "citationKey": "XiaoweiYangMarkovtransition2007", "url": "http://smm.sagepub.com/cgi/content/abstract/16/4/347", "accessDate": "2009-03-29T14:10:11Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0009", "rights": "", "extra": "00013", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:43Z" } }, { "key": "E6WW924V", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/E6WW924V", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/E6WW924V", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Metz et al.", "parsedDate": "1998-01-01", "numChildren": 0 }, "data": { "key": "E6WW924V", "version": 438, "itemType": "journalArticle", "title": "Statistical Comparison of Two ROC-curve Estimates Obtained from Partially-paired Datasets", "creators": [ { "creatorType": "author", "firstName": "Charles E.", "lastName": "Metz" }, { "creatorType": "author", "firstName": "Benjamin A.", "lastName": "Herman" }, { "creatorType": "author", "firstName": "Cheryl A.", "lastName": "Roe" } ], "abstractNote": "The authors propose a new generalized method for ROC-curve fitting and statistical testing that allows researchers to utilize all of the data collected in an experimental comparison of two diagnostic modalities, even if some patients have not been studied with both modalities. Their new algorithm, ROCKIT, subsumes previous algorithms as special cases. It conducts all analyses available from previous ROC software and provides 95% confidence intervals for all estimates. ROCKIT was tested on more than half a million computer-simulated datasets of various sizes and configurations repre senting a range of population ROC curves. The algorithm successfully converged for more than 99.8% of all datasets studied. The type I error rates of the new algorithm's statistical test for differences in Az estimates were excellent for datasets typically en countered in practice, but diverged from alpha for datasets arising from some extreme situations. Key words. receiver operating characteristic (ROC) analysis, maximum-like lihood estimation; partially-paired data; missing data. (Med Decis Making 1998;18: 110-121)", "publicationTitle": "Med Decis Making", "publisher": "", "place": "", "date": "Janvier 1, 1998", "volume": "18", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "110-121", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/0272989X9801800118", "citationKey": "MetzStatisticalComparison1998", "url": "http://mdm.sagepub.com/cgi/content/abstract/18/1/110", "accessDate": "2009-03-29T12:55:14Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0228", "rights": "", "extra": "00310", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:42Z" } }, { "key": "EP9TT66X", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/EP9TT66X", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/EP9TT66X", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Becker et al.", "parsedDate": "1997", "numChildren": 0 }, "data": { "key": "EP9TT66X", "version": 438, "itemType": "journalArticle", "title": "EM algorithms without missing data", "creators": [ { "creatorType": "author", "firstName": "Mark P", "lastName": "Becker" }, { "creatorType": "author", "firstName": "Ilsoon", "lastName": "Yang" }, { "creatorType": "author", "firstName": "Kenneth", "lastName": "Lange" } ], "abstractNote": "Most problems in computational statistics involve optimization of an objective function such as a loglikelihood, a sum of squares, or a log posterior function. The EM algorithm is one of the most effective algorithms for maximization because it iteratively transfers maximization from a complex function to a simple, surrogate function. This theoretical perspective clarifies the operation of the EM algorithm and suggests novel generalizations. Besides simplifying maximization, optimization transfer usually leads to highly stable algorithms with well-understood local and global convergence properties. Although convergence can be excruciatingly slow, various devices exist for accelerating it. Beginning with the EM algorithm, we review in this paper several optimization transfer algorithms of substantial utility in medical statistics.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 1997", "volume": "6", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "38-54", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029700600104", "citationKey": "BeckerEMalgorithms1997", "url": "http://smm.sagepub.com/cgi/content/abstract/6/1/38", "accessDate": "2009-03-29T14:08:41Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0037", "rights": "", "extra": "00056", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:40Z" } }, { "key": "F7AENEJG", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/F7AENEJG", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/F7AENEJG", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Kenward and Molenberghs", "parsedDate": "1999", "numChildren": 0 }, "data": { "key": "F7AENEJG", "version": 438, "itemType": "journalArticle", "title": "Parametric models for incomplete continuous and categorical longitudinal data", "creators": [ { "creatorType": "author", "firstName": "M G", "lastName": "Kenward" }, { "creatorType": "author", "firstName": "G", "lastName": "Molenberghs" } ], "abstractNote": "This paper reviews models for incomplete continuous and categorical longitudinal data. In terms of Rubin's classification of missing value processes we are specifically concerned with the problem of nonrandom missingness. A distinction is drawn between the classes of selection and pattern-mixture models and, using several examples, these approaches are compared and contrasted. The central roles of identifiability and sensitivity are emphasized throughout.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 1999", "volume": "8", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "51-83", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029900800105", "citationKey": "KenwardParametricmodels1999", "url": "http://smm.sagepub.com/cgi/content/abstract/8/1/51", "accessDate": "2009-03-29T14:06:08Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0067", "rights": "", "extra": "00075", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:38Z" } }, { "key": "G2RQBF82", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/G2RQBF82", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/G2RQBF82", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Vermunt", "parsedDate": "2008", "numChildren": 0 }, "data": { "key": "G2RQBF82", "version": 438, "itemType": "journalArticle", "title": "Latent class and finite mixture models for multilevel data sets", "creators": [ { "creatorType": "author", "firstName": "Jeroen K", "lastName": "Vermunt" } ], "abstractNote": "An extension of latent class (LC) and finite mixture models is described for the analysis of hierarchical data sets. As is typical in multilevel analysis, the dependence between lower-level units within higher-level units is dealt with by assuming that certain model parameters differ randomly across higher-level observations. One of the special cases is an LC model in which group-level differences in the logit of belonging to a particular LC are captured with continuous random effects. Other variants are obtained by including random effects in the model for the response variables rather than for the LCs. The variant that receives most attention in this article is an LC model with discrete random effects: higher-level units are clustered based on the likelihood of their members belonging to the various LCs. This yields a model with mixture distributions at two levels, namely at the group and the subject level. This model is illustrated with three rather different empirical examples. The appendix describes an adapted version of the expectation--maximization algorithm that can be used for maximum likelihood estimation, as well as providing setups for estimating the multilevel LC model with generally available software.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 2008", "volume": "17", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "33-51", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/0962280207081238", "citationKey": "VermuntLatentclass2008", "url": "http://smm.sagepub.com/cgi/content/abstract/17/1/33", "accessDate": "2009-03-29T14:02:31Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0019", "rights": "", "extra": "00108", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:37Z" } }, { "key": "GK6C38HA", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/GK6C38HA", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/GK6C38HA", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Dunn and Roberts", "parsedDate": "1999", "numChildren": 0 }, "data": { "key": "GK6C38HA", "version": 438, "itemType": "journalArticle", "title": "Modelling method comparison data", "creators": [ { "creatorType": "author", "firstName": "Graham", "lastName": "Dunn" }, { "creatorType": "author", "firstName": "Chris", "lastName": "Roberts" } ], "abstractNote": "We explore a range of linear regression models that might be useful for either: (a) the relative calibration of two or more methods or (b) to evaluate their precisions relative to each other. Ideally, one should be able to use a single data set to carry out the jobs (a) and (b) together. Throughout this review we consider the constraints (assumptions) needed to attain identifiability of the models and the possible pitfalls to the unwary in having to introduce them. We also pay particular attention to the possible problems arising from the presence of random matrix effects (reproducible random measurement `errors' that are characteristic of a given method when being used on a given specimen or sample, i.e. specimen specific biases or subject by method interactions). Finally, we stress the importance of a fully-informative design (using replicate measurements on each subject using at least three independent methods) and large sample sizes.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Avril 1, 1999", "volume": "8", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "161-179", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029900800205", "citationKey": "DunnModellingmethod1999", "url": "http://smm.sagepub.com/cgi/content/abstract/8/2/161", "accessDate": "2009-03-29T14:53:31Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0026", "rights": "", "extra": "00034", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:35Z" } }, { "key": "GKBTEWA5", "version": 438, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/GKBTEWA5", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/GKBTEWA5", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Raab and Parpia", "parsedDate": "2001", "numChildren": 0 }, "data": { "key": "GKBTEWA5", "version": 438, "itemType": "journalArticle", "title": "Random effects models for HIV marker data: practical approaches with currently available software", "creators": [ { "creatorType": "author", "firstName": "Gillian M", "lastName": "Raab" }, { "creatorType": "author", "firstName": "Tamiza", "lastName": "Parpia" } ], "abstractNote": "The analysis of marker data from HIV positive patients has been the motivation for many new developments in applied statistics. As well as reviewing these methods, this paper considers the extent to which programs to implement them are available in current software. Particular areas of development have been the joint modelling of markers and survival outcomes, non-linear random effects models that are of particular relevance for studying the efficacy of treatments and the use of Bayesian computational methods for inference from marker data. The package Win BUGS is recommended as being particularly well suited to the analysis of marker data.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Avril 1, 2001", "volume": "10", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "101-116", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228020101000203", "citationKey": "RaabRandomeffects2001", "url": "http://smm.sagepub.com/cgi/content/abstract/10/2/101", "accessDate": "2009-03-29T14:55:08Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Random effects models for HIV marker data", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0005", "rights": "", "extra": "00005", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:34Z" } }, { "key": "GXATK8D4", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/GXATK8D4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/GXATK8D4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Barnard and Meng", "parsedDate": "1999", "numChildren": 0 }, "data": { "key": "GXATK8D4", "version": 437, "itemType": "journalArticle", "title": "Applications of multiple imputation in medical studies: from AIDS to NHANES", "creators": [ { "creatorType": "author", "firstName": "John", "lastName": "Barnard" }, { "creatorType": "author", "firstName": "Xiao-Li", "lastName": "Meng" } ], "abstractNote": "Rubin's multiple imputation is a three-step method for handling complex missing data, or more generally, incomplete-data problems, which arise frequently in medical studies. At the first step, m (> 1) completed-data sets are created by imputing the unobserved data m times using m independent draws from an imputation model, which is constructed to reasonably approximate the true distributional relationship between the unobserved data and the available information, and thus reduce potentially very serious nonresponse bias due to systematic difference between the observed data and the unobserved ones. At the second step, m complete-data analyses are performed by treating each completed-data set as a real complete-data set, and thus standard complete-data procedures and software can be utilized directly. At the third step, the results from the m complete-data analyses are combined in a simple, appropriate way to obtain the so-called repeated-imputation inference, which properly takes into account the uncertainty in the imputed values. This paper reviews three applications of Rubin's method that are directly relevant for medical studies. The first is about estimating the reporting delay in acquired immune deficiency syndrome (AIDS) surveillance systems for the purpose of estimating survival time after AIDS diagnosis. The second focuses on the issue of missing data and noncompliance in randomized experiments, where a school choice experiment is used as an illustration. The third looks at handling nonresponse in United States National Health and Nutrition Examination Surveys (NHANES). The emphasis of our review is on the building of imputation models (i.e. the first step), which is the most fundamental aspect of the method.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 1999", "volume": "8", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "17-36", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029900800103", "citationKey": "BarnardApplicationsmultiple1999", "url": "http://smm.sagepub.com/cgi/content/abstract/8/1/17", "accessDate": "2009-03-29T14:56:45Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Applications of multiple imputation in medical studies", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0120", "rights": "", "extra": "00173", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:33Z" } }, { "key": "I59QB5AP", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/I59QB5AP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/I59QB5AP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 121172, "username": "craigmarker", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/craigmarker", "type": "text/html" } } }, "lastModifiedByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "McNally", "parsedDate": "2009-07-01", "numChildren": 0 }, "data": { "key": "I59QB5AP", "version": 437, "itemType": "journalArticle", "title": "Can we fix PTSD in DSM‐V?", "creators": [ { "creatorType": "author", "firstName": "Richard J", "lastName": "McNally" } ], "abstractNote": "", "publicationTitle": "Depression and Anxiety", "publisher": "", "place": "", "date": "2009/07/01", "volume": "26", "issue": "7", "section": "", "partNumber": "", "partTitle": "", "pages": "597-600", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1002/da.20586", "citationKey": "McNallyCanwe2009", "url": "http://onlinelibrary.wiley.com/doi/10.1002/da.20586/abstract", "accessDate": "2012-01-05T14:50:55Z", "PMID": "", "PMCID": "", "ISSN": "1520-6394", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Wiley Online Library", "callNumber": "0026", "rights": "", "extra": "00069", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2012-01-05T14:50:55Z", "dateModified": "2025-01-30T07:37:31Z" } }, { "key": "I7TTK5WU", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/I7TTK5WU", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/I7TTK5WU", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Have et al.", "parsedDate": "2004", "numChildren": 0 }, "data": { "key": "I7TTK5WU", "version": 437, "itemType": "journalArticle", "title": "Deviations from the population-averaged versus cluster-specific relationship for clustered binary data", "creators": [ { "creatorType": "author", "firstName": "Thomas R Ten", "lastName": "Have" }, { "creatorType": "author", "firstName": "Sarah J", "lastName": "Ratcliffe" }, { "creatorType": "author", "firstName": "Beth A", "lastName": "Reboussin" }, { "creatorType": "author", "firstName": "Michael E", "lastName": "Miller" } ], "abstractNote": "There has been much debate about the relative merits of mixed effects and population-averaged logistic models. We present a different perspective on this issue by noting that the investigation of the relationship between these models for a given dataset offers a type of sensitivity analysis that may reveal problems with assumptions of the mixed effects and/or population-averaged models for clustered binary response data in general and longitudinal binary outcomes in particular. We present several datasets in which the following violations of assumptions are associated with departures from the expected theoretical relationship between these two models: 1) negative intra-cluster correlations; 2) confounding of the response-covariate relationship by cluster effects; and 3) confounding of autoregressive relationships by the link between baseline outcomes and subject effects. Under each of these conditions, the expected theoretical attenuation of the population-averaged odds ratio relative to the cluster-specific odds ratio does not necessarily occur. In all cases, the naive fltting of a random intercept logistic model appears to lead to bias. In response, the random intercept model is modified to accommodate negative intra-cluster correlations, confounding due to clusters, or baseline correlations with random effects. Comparisons are made with GEE estimation of population-averaged models and conditional likelihood estimation of cluster-specific models. Several examples, including a cross-over trial, a multicentre nonrandomized treatment study, and a longitudinal observational study are used to illustrate these modiflcations.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Février 1, 2004", "volume": "13", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "3-16", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1191/0962280204sm355ra", "citationKey": "HaveDeviationspopulationaveraged2004", "url": "http://smm.sagepub.com/cgi/content/abstract/13/1/3", "accessDate": "2009-03-29T14:08:16Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0008", "rights": "", "extra": "00014", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:30Z" } }, { "key": "IGA9MBIN", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/IGA9MBIN", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/IGA9MBIN", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Thurigen et al.", "parsedDate": "2000-10-01", "numChildren": 0 }, "data": { "key": "IGA9MBIN", "version": 437, "itemType": "journalArticle", "title": "Measurement error correction using validation data: a review of methods and their applicability in case-control studies", "creators": [ { "creatorType": "author", "firstName": "Dorothee", "lastName": "Thurigen" }, { "creatorType": "author", "firstName": "Donna", "lastName": "Spiegelman" }, { "creatorType": "author", "firstName": "Maria", "lastName": "Blettner" }, { "creatorType": "author", "firstName": "Carsten", "lastName": "Heuer" }, { "creatorType": "author", "firstName": "Hermann", "lastName": "Brenner" } ], "abstractNote": "Measurement error is a serious problem in the analysis of epidemiological data. In the past 20 years, a large number of methods for the correction of measurement error have been developed. While at the beginning mostly methods for cohort studies were considered, recently more attention has been paid to case-control studies. Although a variety of methods have been proposed, they are very rarely used in practice. To stimulate their use and further development, this article provides a comprehensive overview on methods developed for multivariable regression analysis of epidemiologic studies with validation data sets. The methods are systematically classified with respect to the underlying theory. An assessment of prerequisites, assumptions and performance of the available methods is given. Particular attention is paid to applicability to case-control studies and need for further research and development is pointed out.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Octobre 1, 2000", "volume": "9", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "447-474", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228020000900504", "citationKey": "ThurigenMeasurementerror2000", "url": "http://smm.sagepub.com/cgi/content/abstract/9/5/447", "accessDate": "2009-03-29T13:16:32Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Measurement error correction using validation data", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0035", "rights": "", "extra": "00040", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:29Z" } }, { "key": "JZ4CEW6R", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/JZ4CEW6R", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/JZ4CEW6R", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Hui and Zhou", "parsedDate": "1998", "numChildren": 0 }, "data": { "key": "JZ4CEW6R", "version": 437, "itemType": "journalArticle", "title": "Evaluation of diagnostic tests without gold standards", "creators": [ { "creatorType": "author", "firstName": "Siu L", "lastName": "Hui" }, { "creatorType": "author", "firstName": "Xiao H", "lastName": "Zhou" } ], "abstractNote": "This paper reviews statistical methods developed to estimate the sensitivity and specificity of screening or diagnostic tests when the fallible tests are not evaluated against a gold standard. It gives a brief summary of the earlier historical developments and focuses on the more recent methods. It covers Bayesian approaches and longitudinal studies with repeated testing. In particular, it reviews the procedures that do not require the assumption of independence between tests conditional on the true disease status.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Août 1, 1998", "volume": "7", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "354-370", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1177/096228029800700404", "citationKey": "HuiEvaluationdiagnostic1998", "url": "http://smm.sagepub.com/cgi/content/abstract/7/4/354", "accessDate": "2009-03-29T13:57:34Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0123", "rights": "", "extra": "00169", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:25Z" } }, { "key": "N7PZP5W6", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/N7PZP5W6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/N7PZP5W6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Troxel", "parsedDate": "2002", "numChildren": 0 }, "data": { "key": "N7PZP5W6", "version": 437, "itemType": "journalArticle", "title": "Techniques for incorporating longitudinal measurements into analyses of survival data from clinical trials", "creators": [ { "creatorType": "author", "firstName": "A B", "lastName": "Troxel" } ], "abstractNote": "This article reviews existing approaches for joint analysis of longitudinal measurements, possibly measured with error or incompletely observed, and event-time data, possibly censored. The models take the form of selection or pattern-mixture models; estimation proceeds via the EM algorithm or Bayesian sampling techniques. The models are compared, their estimation and inferential procedures described, and advantages and disadvantages noted. Examples are discussed from several disease areas, including cancer and AIDS.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Juin 1, 2002", "volume": "11", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "237-245", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1191/0962280202sm285ra", "citationKey": "TroxelTechniquesincorporating2002", "url": "http://smm.sagepub.com/cgi/content/abstract/11/3/237", "accessDate": "2009-03-29T14:10:31Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0006", "rights": "", "extra": "00007", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:23Z" } }, { "key": "QDVSQUTJ", "version": 437, "library": { "type": "group", "id": 500, "name": "Structural equation modeling in medical research and primary care", "links": { "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/500/items/QDVSQUTJ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/structural_equation_modeling_in_medical_research_and_primary_care/items/QDVSQUTJ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 18351, "username": "gavenin", "name": "Guillaume AVENIN", "links": { "alternate": { "href": "https://www.zotero.org/gavenin", "type": "text/html" } } }, "creatorSummary": "Manton et al.", "parsedDate": "2004-10-01", "numChildren": 0 }, "data": { "key": "QDVSQUTJ", "version": 437, "itemType": "journalArticle", "title": "Fuzzy set analyses of genetic determinants of health and disability status", "creators": [ { "creatorType": "author", "firstName": "Kenneth G", "lastName": "Manton" }, { "creatorType": "author", "firstName": "XiLiang", "lastName": "Gu" }, { "creatorType": "author", "firstName": "Hai", "lastName": "Huang" }, { "creatorType": "author", "firstName": "Mikhail", "lastName": "Kovtun" } ], "abstractNote": "Analyses of complex genotype-phenotype relations require new statistical procedures because of the potentially high dimensionability of those relations which are expressed with both measurement error and stochasticity in the correlation function. We propose modifying a multivariate procedure called grade of membership (GoM) analysis to deal with the special problems of such analyses. In doing so, we make clear some special features of the GoM model for multivariate analysis of high dimensional, discrete data. This is illustrated for apolipoprotein E (APOE) assessments made on 1805 people in the 1999 National Long Term Care Survey. A number of interesting relations with APOE polymorphism were found where disability profiles were more predictive than specific diagnoses because they implicitly contained information on chronicity and severity of disease processes.", "publicationTitle": "Statistical Methods in Medical Research", "publisher": "", "place": "", "date": "Octobre 1, 2004", "volume": "13", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "395-408", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1191/0962280204sm374ra", "citationKey": "MantonFuzzyset2004", "url": "http://smm.sagepub.com/cgi/content/abstract/13/5/395", "accessDate": "2009-03-29T14:53:58Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Sage Journals Online", "callNumber": "0013", "rights": "", "extra": "00015", "tags": [ { "tag": "#nosource" }, { "tag": "/unread", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2009-05-31T06:45:24Z", "dateModified": "2025-01-30T07:37:21Z" } } ]