Development of the Inventory of College Students' Resilience and evaluating the measurement invariance

In order to help students adapt well to stressful situations or adversity, many researchers have explored the issue of students' resilience. The main purpose of this study was to develop the Inventory of College Students' Resilience (ICSR), for assessing resilience of college students. The present study recruited 993 participants to conduct item analysis, exploratory factor analysis and reliability analysis. We then administered the questionnaire to another 1490 participants in order to conduct confirmatory factor analysis and assess criterion-related validity. The results showed the proposed model fit the data well and the ICSR had both internal consistency and criterion-related validity. The ICSR was also found to have measurement invariance across gender. We conclude that the ICSR can help students to identify strengths and weaknesses in order to reinforce their resilience and improve their response to life stress and trauma.     

Consequences of Ignoring Guessing Effects on Measurement Invariance Analysis

Pseudo-guessing parameters are present in item response theory applications for many educational assessments. When sample size is not sufficiently large, the guessing parameters may be ignored from the analysis. This study examines the impact of ignoring pseudo-guessing parameters on measurement invariance analysis, specifically, on item difficulty, item discrimination, and mean and variance of ability distribution. Results show that when non-zero guessing parameters are ignored from the measurement invariance analysis, item discrimination estimates tend to decrease particularly for more difficult items, and item difficulty estimates decrease unless the items are highly discriminating and difficult. As the guessing parameter increases, the size of the decrease in item discrimination and difficulty tends to increase, and the estimated mean and variance of ability distribution tend to be inaccurate. When two groups have heterogeneous ability distributions, ignoring the guessing parameter affects the reference group and the focal group differently. Implications of result findings are discussed.     

Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony

Abstract

CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors). Exploratory structural equation modeling (ESEM) represents a compromise between exploratory factor analysis’ (EFA) flexibility, and CFA/SEM’s rigor and parsimony, but lacks parsimony (particularly in large models) and might confound constructs that need to be kept separate. In Set-ESEM, two or more a priori sets of constructs are modeled within a single model such that cross-loadings are permissible within the same set of factors (as in Full-ESEM) but are constrained to be zero for factors in different sets (as in CFA). The different sets can reflect the same set of constructs on multiple occasions, and/or different constructs measured within the same wave. Hence, Set-ESEM that represents a middle-ground between the flexibility of traditional-ESEM (hereafter referred to as Full-ESEM) and the rigor and parsimony of CFA/SEM. Thus, the purposes of this article are to provide an overview tutorial on Set-ESEM, juxtapose it with Full-ESEM, and to illustrate its application with simulated data and diverse “real” data applications with accessible, heuristic explanations of best practice.     

Factorial validity of the Utrecht Work Engagement Scale (UWES) across occupational groups in Norway

Nerstad, C.G.L., Richardsen, A.M. & Martinussen, M. (2009). Factorial validity of the Utrecht Work Engagement Scale (UWES) across occupational groups in Norway. Scandinavian Journal of Psychology. The present study investigated the factorial validity of the Utrecht Work Engagement Scale (UWES) among 1266 participants from ten different occupational groups. Confirmatory factor analyses of the total sample, as well as multi‐group analyses and analyses of each of the ten occupational groups separately, indicated that a three‐dimensional model of both the UWES‐17 and the short version, UWES‐9, provided a better fit to the data than a one‐ and two‐dimensional model. The results of multi‐group analyses and analyses of each of the groups separately, indicated that with a few exceptions, the three‐factor model of work engagement provided the best fit. Results indicated factorial invariance and the internal consistencies were acceptable. The fit of the UWES‐9 was slightly better than the UWES‐17. It is concluded that the Norwegian short version may be recommended over the UWES‐17.     

Testing Differential Item Functioning in Small Samples

Abstract

Differential item functioning (DIF) is a pernicious statistical issue that can mask true group differences on a target latent construct. A considerable amount of research has focused on evaluating methods for testing DIF, such as using likelihood ratio tests in item response theory (IRT). Most of this research has focused on the asymptotic properties of DIF testing, in part because many latent variable methods require large samples to obtain stable parameter estimates. Much less research has evaluated these methods in small sample sizes despite the fact that many social and behavioral scientists frequently encounter small samples in practice. In this article, we examine the extent to which model complexity—the number of model parameters estimated simultaneously—affects the recovery of DIF in small samples. We compare three models that vary in complexity: logistic regression with sum scores, the 1-parameter logistic IRT model, and the 2-parameter logistic IRT model. We expected that logistic regression with sum scores and the 1-parameter logistic IRT model would more accurately estimate DIF because these models yielded more stable estimates despite being misspecified. Indeed, a simulation study and empirical example of adolescent substance use show that, even when data are generated from / assumed to be a 2-parameter logistic IRT, using parsimonious models in small samples leads to more powerful tests of DIF while adequately controlling for Type I error. We also provide evidence for minimum sample sizes needed to detect DIF, and we evaluate whether applying corrections for multiple testing is advisable. Finally, we provide recommendations for applied researchers who conduct DIF analyses in small samples.     

Scale horizons in analytic hierarchies

In the light of the many criticisms to which the analytic hierarchy process (AHP) of Saaty has been subjected, the authors have produced a refined version, the modified analytic hierarchy process. This paper develops further the ideas behind the modified process and illustrates with examples some of the difficulties in the AHP and their resolution.     

Psychophysics and the anisotropy of time

In psychophysics, experimental control over the presented stimuli is an important prerequisite. Due to the anisotropy of time, this prerequisite is not given in psychophysical experiments on time perception. Many important factors (e.g., the direction of perceived time flow) cannot be manipulated in timing experiments. The anisotropy of time is a peculiarity, which distinguishes the time dimension from other perceptual qualities.Here I summarize the anisotropy-related differences between the perception of time and the perception of other qualities. It is discussed to what extent these differences might affect results and interpretations in psychophysical experiments. In conclusion, I argue for a ‘view from nowhen’ on the psychophysical study of time perception.     

Testing the factor structure of the Forgiveness Scale among Italian adolescent students

ABSTRACT

The aim of the present study was to analysis the factor structure of the Italian version of the Forgiveness Scale (FS) among 663 adolescent students in Italy. The FS involves of 15 items measuring forgiveness toward the wrongdoer. This scale comprises two subscales, Absence of Negative (AN) and Presence of Positive (PP). These subscales evaluate the absence of negative and the existence of positive emotions, thoughts, and behavioural inclinations. Results suggests that only 11 of the original items are valid in the Italian version of the FS. In contrast to the original study, the two dimensions of forgiveness (AN and PP) were independent of each other in the current analysis. Evidence for convergent validity was also found. The results provide some initial support for the bi-dimensionality and internal consistency of the Italian FS and offer a starting point for future research to be pursued in forgiveness.