Zusammenfassung. Der SF-12 stellt die Kurzform der Short Form 36 Health Survey dar. Ein wenig beachteter Nachteil im Algorithmus zur Bildung der Skalenindizes liegt darin, dass die Bildung der Skalenwerte nur dann empfohlen wird, wenn alle Items von einer ...
An Introduction to the Plausible Value Technique for Psychological ResearchAbstract. In psychological research, the assessment of most constructs is affected by measurement error. Measurement error results in biased estimates of population parameters and ...
Handling of missing data in psychological research: Problems and solutionsAbstract. Missing data are a pervasive problem in empirical psychological research. From the methodological perspective, traditional procedures such as Casewise and Pairwise ...
Analysis of longitudinal data: Application of hierarchical linear modelsAbstract.Background: Longitudinal data arise frequently in clinical psychology and in psychiatric research. These data are most often analyzed using a repeated-measures analysis of ...
This article concerns methodology for testing the significance of differences in mean rates of change in controlled repeated measurements designs with limited sample sizes, autoregressive error structures, nonlinear patterns of underlying true mean change,...
The local influence diagnostics, proposed by Cook (1986), provide a flexible way to assess the impact of minor model perturbations on key model parameters’ estimates. In this paper, we apply the local influence idea to the detection of test speededness in ...
Imputation of incomplete questionnaire items should preserve the structure among items and the correlations between scales. This paper explores the use of fully conditional specification (FCS) to impute missing data in questionnaire items. FCS is ...
Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient ...
Abstract. A multivariate multilevel model (MVMM) extends standard multilevel modeling by including multiple dependent variables and thus could be used in place of traditional multivariate analyses. For a two-group study with two correlated ...
Abstract. Dyadic data often appear in social and behavioral research, and multilevel models (MLMs) can be used to analyze them. For dyadic data, the group size is 2, which is the minimum group size we could have for fitting a multilevel ...
Abstract. The analysis of variance (ANOVA) is frequently used to examine whether a number of groups differ on a variable of interest. The global hypothesis test of the ANOVA can be reformulated as a regression model in which all group ...
Abstract. Predictive mean matching (PMM) is a state-of-the-art hot deck multiple imputation (MI) procedure. The quality of its results depends, inter alia, on the availability of suitable donor cases. Applying PMM in small sample scenarios ...
Abstract. Latent class analysis has been recently proposed for the multiple imputation (MI) of missing categorical data, using either a standard frequentist approach or a nonparametric Bayesian model called Dirichlet process mixture of ...