On summary measure analysis of linear trend repeated measures data: performance comparison with two competing methods.

Background: The summary measure approach (SMA) is sometimes the only applicable tool for the analysis of repeated measurements in medical research, especially when the number of measurements is relatively large. This study aimed to describe techniques based on summary measures for the analysis of linear trend repeated measures data and then to compare performances of SMA, linear mixed model (LMM), and unstructured multivariate approach (UMA).

Methods: Practical guidelines based on the least squares regression slope and mean of response over time for each subject were provided to test time, group, and interaction effects.

A simple powerful bivariate test for two sample location problems in experimental and observational studies.

Background: In many areas of medical research, a bivariate analysis is desirable because it simultaneously tests two response variables that are of equal interest and importance in two populations. Several parametric and nonparametric bivariate procedures are available for the location problem but each of them requires a series of stringent assumptions such as specific distribution, affine-invariance or elliptical symmetry. The aim of this study is to propose a powerful test statistic that requires none of the aforementioned assumptions.