Title: Sample size calculations for model validation in linear regression analysis
Authors: Jan, Show-Li
Shieh, Gwowen
管理科學系
Department of Management Science
Keywords: Linear regression;Model validation;Power;Sample size;Stochastic predictor
Issue Date: 12-Mar-2019
Abstract: BackgroundLinear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients.MethodsThe purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis.ResultsA fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures.ConclusionsThe results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness.
URI: http://dx.doi.org/10.1186/s12874-019-0697-9
http://hdl.handle.net/11536/149031
ISSN: 1471-2288
DOI: 10.1186/s12874-019-0697-9
Journal: BMC MEDICAL RESEARCH METHODOLOGY
Volume: 19
Appears in Collections:Articles