Journal ArticleDOI
Performance of logistic regression modeling: beyond the number of events per variable, the role of data structure.
Delphine S. Courvoisier,Christophe Combescure,Thomas Agoritsas,Angèle Gayet-Ageron,Thomas V. Perneger +4 more
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TLDR
There is no single rule based on EPV that would guarantee an accurate estimation of logistic regression parameters, so the number of predictors, probable size of the regression coefficients based on previous literature, and correlations among the predictors must be taken into account as guidelines to determine the necessary sample size.About:Â
This article is published in Journal of Clinical Epidemiology.The article was published on 2011-09-01. It has received 235 citations till now. The article focuses on the topics: Multicollinearity & Logistic regression.read more
Citations
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Journal ArticleDOI
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration.
Karel G.M. Moons,Douglas G. Altman,Johannes B. Reitsma,John P. A. Ioannidis,Petra Macaskill,Ewout W. Steyerberg,Andrew J. Vickers,David F. Ransohoff,Gary S. Collins +8 more
TL;DR: In virtually all medical domains, diagnostic and prognostic multivariable prediction models are being developed, validated, updated, and implemented with the aim to assist doctors and individuals in estimating probabilities and potentially influence their decision making.
Journal ArticleDOI
Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist.
Karel G.M. Moons,Joris A. H. de Groot,Walter Bouwmeester,Yvonne Vergouwe,Susan Mallett,Douglas G. Altman,Johannes B. Reitsma,Gary S. Collins +7 more
TL;DR: Carl Moons and colleagues provide a checklist and background explanation for critically appraising and extracting data from systematic reviews of prognostic and diagnostic prediction modelling studies.
Journal ArticleDOI
Variable selection - A review and recommendations for the practicing statistician.
TL;DR: In this article, the authors provide an overview of variable selection methods that are based on significance or information criteria, penalized likelihood, change-in-estimate criterion, background knowledge, or combinations thereof.
Journal ArticleDOI
The number of subjects per variable required in linear regression analyses
TL;DR: Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals.
Journal ArticleDOI
Calculating the sample size required for developing a clinical prediction model.
Richard D Riley,Joie Ensor,Kym I E Snell,Frank E. Harrell,Glen P. Martin,Johannes B. Reitsma,Karel G.M. Moons,Gary S. Collins,Maarten van Smeden,Maarten van Smeden,Maarten van Smeden +10 more
TL;DR: In this article, the authors provide guidance on how to calculate the sample size required to develop a clinical prediction model.
References
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Journal ArticleDOI
Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
TL;DR: In this article, an easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, which are particularly needed for binary, ordinal, and time-to-event outcomes.
BookDOI
Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis
TL;DR: In this article, the authors present a case study in least squares fitting and interpretation of a linear model, where they use nonparametric transformations of X and Y to fit a linear regression model.
Journal ArticleDOI
A simulation study of the number of events per variable in logistic regression analysis.
Peter Peduzzi,John Concato,John Concato,Elizabeth Kemper,Elizabeth Kemper,Theodore R. Holford,Alvan R. Feinstein,Alvan R. Feinstein +7 more
TL;DR: Findings indicate that low EPV can lead to major problems, and the regression coefficients were biased in both positive and negative directions, and paradoxical associations (significance in the wrong direction) were increased.
Book ChapterDOI
Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors
TL;DR: An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.
Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
Kerry L. Lee,Daniel B. Mark +1 more
TL;DR: An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, which are applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.