Publications

Background Unaccompanied young refugees constitute an especially vulnerable population, reporting high rates of trauma and mental health problems. There is a significant gap in the literature on trauma and posttraumatic stress symptoms (PTSS) in unaccompanied young refugees who are still on the move and live in precarious circumstances such as refugee camps. This study therefore aimed to contribute to this gap by investigating pre- and ...

Growth curve modeling is commonly used in psychological, educational, and social science research. The mainstream estimators for growth curve modeling are based on normal theory, but real data are unlikely to be exactly normally distributed. To improve estimation and inference with non-normal data, various estimators have been proposed. Among these estimators, the asymptotically distribution free (ADF) estimator does not need to rely on any ...

There have been considerable methodological developments of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple hypotheses simultaneously, the ability to test complex hypotheses involving equality as well as order constraints on the parameters of interest, and the interpretability of the outcome as the weight of ...

We propose a two-step procedure to estimate structural equation models (SEMs). In a first step, the latent variable is replaced by its conditional expectation given the observed data. This conditional expectation is estimated using a James-Stein type shrinkage estimator. The second step consists of regressing the dependent variables on this shrinkage estimator. In addition to linear SEMs, we also derive shrinkage estimators to estimate ...

Using the EffectLiteR framework, researchers can test classical null hypotheses about effects of interest via Wald and F-tests, while taking into account the stochastic nature of group sizes. This paper aims at extending EffectLiteR to test informative hypotheses, assuming for example that the average effect of a new treatment is greater than the average effect of an old treatment, which in turn is greater than zero. We present a simulated data ...

This paper discusses maximum likelihood estimation for two-level structural equation models when data are missing at random at both levels. Building on existing literature, a computationally efficient expression is derived to evaluate the observed log-likelihood. Unlike previous work, the expression is valid for the special case where the model implied varianceU+2013covariance matrix at the between level is singular. Next, the log-likelihood ...

We propose an extension of the WilcoxonU+2013MannU+2013Whitney test to compare two groups when the outcome variable is latent. We empirically demonstrate that the test can have superior power properties relative to tests based on Structural Equation Modeling for a variety of settings. In addition, several other advantages of the WilcoxonU+2013MannU+2013Whitney test are retained such as robustness to outliers and good small sample performance. We ...

This Teacher's Corner paper introduces Bayesian evaluation of informative hypotheses for structural equation models, using the free open-source R packages bain, for Bayesian informative hypothesis testing, and lavaan, a widely used SEM package. The introduction provides a brief non-technical explanation of informative hypotheses, the statistical underpinnings of Bayesian hypothesis evaluation, and the bain algorithm. Three tutorial examples ...

A Correction to this paper has been published

Many researchers have specific expectations about the relation between the means of different groups or between (standardized) regression coefficients. For example, in an experimental setting, the comparison of two or more treatment groups may be subject to order constraints (e.g., H 1: µ1 < µ2 < µ3 = µ4). In practice, hypothesis H 1 is usually tested using a classical one-way ANOVA with additional pairwise comparisons if the corresponding ...