Abstract Background Linear 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. Methods The 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. Results A 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 per...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
ABSTRACT: This article presents methods for sample size and power calculations for studies involving...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
A common question asked by researchers using regression models is, What sample size is needed for my...
In general linear models for categorical data analysis, goodness-of-fit statistics only provide a br...
Regressions and meta-regressions are widely used to estimate patterns and effect sizes in various di...
Clinical prediction models provide individualized outcome predictions to inform patient counseling a...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
Introduction Sample size “rules-of-thumb” for external validation of clinical prediction models sugg...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
In this article, we present a method for sample size calculation for studies involving both the inte...
ABSTRACT: This article presents methods for sample size and power calculations for studies involving...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
A common question asked by researchers using regression models is, What sample size is needed for my...
In general linear models for categorical data analysis, goodness-of-fit statistics only provide a br...
Regressions and meta-regressions are widely used to estimate patterns and effect sizes in various di...
Clinical prediction models provide individualized outcome predictions to inform patient counseling a...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
Introduction Sample size “rules-of-thumb” for external validation of clinical prediction models sugg...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
The primary objective is sample size estimation in linear mixed model settings. Sample size estimati...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...