Responding to mentalization invitations in psychotherapy sessions-A conversation analysis approach.

Objective: Increase in the capacity to mentalize has been proposed to be an important mechanism of change in psychotherapy. However, mentalization has primarily been studied as an individual skill that people either possess or lack, rather than as an interactional phenomenon.

Method: In this study, excerpts from three different sessions in a therapy that aimed at increasing the patients mentalizing capacity were identified and studied using conversation analysis.

Error, power, and cluster separation rates of pairwise multiple testing procedures.

In comparing multiple treatments, 2 error rates that have been studied extensively are the familywise and false discovery rates. Different methods are used to control each of these rates. Yet, it is rare to find studies that compare the same methods on both of these rates, and also on the per-family error rate, the expected number of false rejections.

MODERN REGRESSION METHODS THAT CAN SUBSTANTIALLY INCREASE POWER AND PROVIDE A MORE ACCURATE UNDERSTANDING OF ASSOCIATIONS.

During the last half century hundreds of papers published in statistical journals have documented general conditions where reliance on least squares regression and Pearson's correlation can result in missing even strong associations between variables. Moreover, highly misleading conclusions can be made, even when the sample size is large. There are, in fact, several fundamental concerns related to non-normality, outliers, heteroscedasticity, and curvature that can result in missing a strong association.

Many tests of significance: new methods for controlling type I errors.

There have been many discussions of how Type I errors should be controlled when many hypotheses are tested (e.g., all possible comparisons of means, correlations, proportions, the coefficients in hierarchical models, etc.

Effect of non-normality on test statistics for one-way independent groups designs.

The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous).