Sample Size for Joint Testing of Indirect Effects

Bayesian Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data

A longitudinal study refers to collection of a response variable and possibly some explanatory variables at multiple follow-up times. In many clinical studies with longitudinal measurements, the response variable, for each patient is collected as long as an event of interest, which considered as clinical end point, occurs. Joint modeling of continuous longitudinal measurements and survival time...

Optimal Sample Size for Multiple Testing :

Sample size determination for logistic regression

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 regr...

Comparing two Formulas of Sample Size Determination for Prevalence Studies

Background and purpose: Sample size and its determination is one of the most important problems in health researches. Calculating sample size for prevalence studies is one of the common questions of sample size topics. Minimum sample size with least complexity is desirable in order to achieve the basic goal of these studies. This study aims to compare two formulas of sample size calculation for...

Sample Size Estimation for (Bio)equivalence Testing Between Two Treatments

Standard 2X2 and replicated 2X2m crossover designs are recommended in the regulatory guidelines to establish bioequivalence of generic drug with off patent brand-name drug. Estimation of sample size, in any clinical trial, targets to optimize the resource usage with assurance of having adequate probability (power) to get significant result. This paper discusses the statistical concept behind sa...