A modified Armitage test for more than a linear trend on proportions

TL;DR

This paper introduces a modified Armitage test using a multiple marginal model approach to enhance power across various dose-response relationships in proportions, applicable to different effect sizes and data structures.

Contribution

It presents a novel modification of the Armitage test that accommodates multiple dose score models and extends to generalized linear models with practical R package support.

Findings

Enhanced power against diverse dose-response patterns

Flexible application to various effect sizes and data types

Practical implementation via the tukeytrend R package

Abstract

The Armitage test for linear trend in proportions can be modified using the multiple marginal model approach for three regression models with arithmetic, ordinal and logarithmic dose scores simultaneously, to be powerful against a wide range of possible dose response relationships. Moreover, it can be used for particular designs in the generalized linear (mixed) model for the three common effect sizes odds ratio, risk ratio and risk difference. The related R package tukeytrend allows simple generalizations, e.g. the analysis 2-by-k table data with a possible plateau shape or analysing overdispersed proportions. The evaluation of further real data examples are available in a vignette to that R package.