Sample size determination for logistic regression

Sample size determination for logistic regression

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Article ID: iaor20141432
Volume: 255
Issue: 12
Start Page Number: 743
End Page Number: 752
Publication Date: Jan 2014
Journal: Journal of Computational and Applied Mathematics
Authors: , ,
Keywords: logistic regression
Abstract:

The problem of sample size estimation is important in medical applications, especially in cases of expensive measurements of immune biomarkers. This paper describes the problem of logistic regression analysis with the sample size determination algorithms, namely the methods of univariate statistics, logistics regression, cross‐validation and Bayesian inference. The authors, treating the regression model parameters as a multivariate variable, propose to estimate the sample size using the distance between parameter distribution functions on cross‐validated data sets. Herewith, the authors give a new contribution to data mining and statistical learning, supported by applied mathematics.

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