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Clinical trials are common in medical research where multiple non-Gaussianresponses and time-dependent observations are frequent. The analysis of datafrom these studies requires statistical modeling techniques that take thesecharacteristics into account. We propose a general strategy based on the Waldstatistics to perform hypothesis tests like ANOVAs, MANOVAs and multiplecomparison tests on regression and dispersion parameters of multivariatecovariance generalized linear models (McGLMs). McGLMs provide a generalstatistical modeling framework for normal and non-normal multivariate dataanalysis along with a wide range of correlation structures. We design differentsimulation scenarios to verify the properties of the proposed tests. Theresults are promising showing that the proposed tests present the levels ofconfidence close to the specified one for all simulation study scenarios.Complementary to the proposal, we developed implementations in the R languageto carry out the tests presented, the codes are available in the supplementarymaterial. The proposal is motivated by the analysis of a clinical trial thataims to evaluate the effect of the use of probiotics in the control ofaddiction and binge eating disorder in patients undergoing bariatric surgery.The subjects were separated into two groups (placebo and treatment) andevaluated at three different times. The results indicate that addiction andbinge eating disorder reduce over time, but there is no difference betweengroups at each time point.

Hypothesis tests for multiple responses regression: effect of probiotics on addiction and binge eating disorder