In this article, we present a method for sample size calculation for studies involving both the intercept and slope parameters of a simple linear regression model. Some methods have been proposed in the literature to determine the adequate sample size. However, they are usually based on the line slope only. We propose a method based on the F statistic that involves both the intercept and the slope parameters of the model. The validation process is conducted by fitting a simple linear regression model and by testing a zero intercept and unity slope hypothesis. Compared to a traditional method and using Monte Carlo simulations, encouraging results attest for the clear superiority of the proposed method. The article ends with a real-life examp...
importance to assure that the presence of a difference of medical importance is detected. For a give...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...
[[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...
Abstract Background Linear regression analysis is a widely used statistical technique in practical a...
ABSTRACT: This article presents methods for sample size and power calculations for studies involving...
A common question asked by researchers using regression models is, What sample size is needed for my...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
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...
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...
<p>In case of small samples, asymptotic confidence sets may be inaccurate, with their actual coverag...
importance to assure that the presence of a difference of medical importance is detected. For a give...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...
[[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...
Abstract Background Linear regression analysis is a widely used statistical technique in practical a...
ABSTRACT: This article presents methods for sample size and power calculations for studies involving...
A common question asked by researchers using regression models is, What sample size is needed for my...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
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...
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...
<p>In case of small samples, asymptotic confidence sets may be inaccurate, with their actual coverag...
importance to assure that the presence of a difference of medical importance is detected. For a give...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...
[[abstract]]Linearity is one of the most important characteristics for evaluation of the accuracy in...