BACKGROUND It has generally been argued that parametric statistics should not be applied to data with non-normal distributions. Empirical research has demonstrated that Mann-Whitney generally has greater power than the t-test unless data are sampled from the normal. In the case of randomized trials, we are typically interested in how an endpoint, such as blood pressure or pain, changes followin...

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate...

A grouping or blocking of observations can be achieved by using categorical or dummy variables. Examples of categorical variables include gender, country of origin, job title and experimental treatment. This should be contrasted with ordinal variables, such as age class, highest degree attained or a score on a 5-point scale with values comprised between strongly agree and strongly disagree. The...

BACKGROUND Analysis of change in health status using data from two waves can be examined either adjusted or unadjusted for baseline health status. The effect of socioeconomic position (SEP) on cognitive change was assessed using both these strategies and the implications of the analyses are discussed. METHODS Data from 1261 men and 483 women of the Whitehall II cohort study, aged 50-55 years ...