MacDonald and Gardner reported the results of a comparative study of two post hoc cellwise tests in 3 X 4 contingency tables under the independence and homogeneity models. Based on their results, they advised against the use of standardized residuals and in favor of adjusted residuals. Here the authors show that the comparison was biased in favor of adjusted residuals because of a failure to consider the nonunit variance of standardized residuals. The authors define a moment-corrected standardized residual that overcomes this bias and present the results of a thorough study including two-way tables of all dimensions between 2 X 2 and 8 X 12 that aimed at comparing moment-corrected standardized residuals with adjusted residuals. Across the entire set of table dimensions included in this study, the results reveal that both residuals yield essentially the same pat-tern of cell-by-cell and experimentwise Type I error rates when the data come from variables with uniform marginal distributions. When the data come from variables with peaked marginal distributions, adjusted residuals behave minimally better than moment-corrected residuals.

Alc, BIC, covariance structure, longitudinal data, mean structure, repeated measures, RLRT, 62J05, 62F10, 62P10,

This paper describes a method proposed for a censored linear regression model that can be used in the context of survival analysis. The method has the important characteristic of allowing estimation and inference without knowing the distribution of the duration variable. Moreover, it does not need the assumption of proportional hazards. Therefore, it can be an interesting alternative to the Cox proportional hazards models when this assumption does not hold. In addition, implementation and interpretation of the results is simple. In order to analyse the performance of this methodology, we apply it to two real examples and we carry out a simulation study. We present its results together with those obtained with the traditional Cox model and AFT parametric models. The new proposal seems to lead to more precise results.

No abstract