Statistics in medicine
-
Statistics in medicine · Oct 2000
Comparative StudyTesting whether treatment is 'better' than control with ordered categorical data: an evaluation of new methodology.
A new test procedure is presented for the problem of testing whether a treatment is better than a control when there is ordered categorical data. The new test is based on the methodology developed for general 'one-sided' alternatives by Cohen and Sackrowitz. ⋯ As predicted by the theoretical work by Cohen and Sackrowitz, the new test is seen to be preferable to the Wilcoxon-Mann-Whitney test. Computer programs to assist implementation of the new test are made available.
-
Statistics in medicine · Oct 2000
Comparative StudyAnalysis of a cluster randomized trial with binary outcome data using a multi-level model.
The use of multi-level logistic regression models was explored for the analysis of data from a cluster randomized trial investigating whether a training programme for general practitioners' reception staff could improve women's attendance at breast screening. Twenty-six general practices were randomized with women nested within them, requiring a two-level model which allowed for between-practice variability. Comparisons were made with fixed effect (FE) and random effects (RE) cluster summary statistic methods, ordinary logistic regression and a marginal model based on generalized estimating equations with robust variance estimates. ⋯ Estimates of the variance components were of particular interest in this example. Additionally, parametric bootstrap methods within the multi-level model framework provide confidence intervals for these variance components, as well as a confidence interval for the effect of intervention which allows for the imprecision in the estimated variance components. The assumption of normality of the random effects can be checked, and the models extended to investigate multiple sources of variability.