The Tukey trend test: Multiplicity adjustment using multiple marginal models

Bayesian causality measures for multiple ARCH models using marginal likelihoods

Scaled marginal models for multiple continuous outcomes.

In studies that involve multivariate outcomes it is often of interest to test for a common exposure effect. For example, our research is motivated by a study of neurocognitive performance in a cohort of HIV-infected women. The goal is to determine whether highly active antiretroviral therapy affects different aspects of neurocognitive functioning to the same degree and if so, to test for the tr...

Cochran-Armitage Trend Test Using SAS

In clinical trials, a dose response study is often conducted to investigate the relationship between increasing dosage and the effect of the drug under study. The Cochran-Armitage trend test is commonly used to study the underlying trend. This paper summarizes various SAS procedures, including PROC FREQ, PROC MULTTEST, and PROC LOGISTIC, which perform the trend test when the response is binary....

Multiplicity adjustment for composite binary endpoints.

BACKGROUND Binary composite outcome measures are increasingly used as primary endpoints in clinical trials. Composite endpoints combine several events of interest within a single variable. However, as the effect observed for the composite does not necessarily reflect the effects for the individual components, it is recommended in the literature to additionally evaluate each component separately...

Using the Tukey-Kramer omnibus test in the Hayter-Fisher procedure.

Using Tukey-Kramer versus the ANOVA F-test as the omnibus test of the Hayter-Fisher procedure for comparing all pairs of normally distributed means, when sample sizes are unequal, is investigated. Simulation results suggest that using Tukey-Kramer leads to as much or more any-pairs power compared to using the F-test for certain patterns of mean differences, and equivalent per-pair and all-pairs...