Ulrich Trautwein

Bio: Ulrich Trautwein is an academic researcher from University of Tübingen. The author has contributed to research in topics: Academic achievement & Big Five personality traits. The author has an hindex of 74, co-authored 364 publications receiving 19330 citations. Previous affiliations of Ulrich Trautwein include University of Illinois at Urbana–Champaign & Max Planck Society.

Academic Self‐Concept, Interest, Grades, and Standardized Test Scores: Reciprocal Effects Models of Causal Ordering

Abstract: Reciprocal effects models of longitudinal data show that academic self-concept is both a cause and an effect of achievement. In this study this model was extended to juxtapose self-concept with academic interest. Based on longitudinal data from 2 nationally representative samples of German 7th-grade students (Study 1: N = 5,649, M age = 13.4; Study 2: N = 2,264, M age = 13.7 years), prior self-concept significantly affected subsequent math interest, school grades, and standardized test scores, whereas prior math interest had only a small effect on subsequent math self-concept. Despite stereotypic gender differences in means, linkages relating these constructs were invariant over gender. These results demonstrate the positive effects of academic self-concept on a variety of academic outcomes and integrate self-concept with the developmental motivation literature.

Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching

Abstract: This study is a methodological-substantive synergy, demonstrating the power and flexibility of exploratory structural equation modeling (ESEM) methods that integrate confirmatory and exploratory factor analyses (CFA and EFA), as applied to substantively important questions based on multidimentional students' evaluations of university teaching (SETs). For these data, there is a well established ESEM structure but typical CFA models do not fit the data and substantially inflate correlations among the nine SET factors (median rs = .34 for ESEM, .72 for CFA) in a way that undermines discriminant validity and usefulness as diagnostic feedback. A 13-model taxonomy of ESEM measurement invariance is proposed, showing complete invariance (factor loadings, factor correlations, item uniquenesses, item intercepts, latent means) over multiple groups based on the SETs collected in the first and second halves of a 13-year period. Fully latent ESEM growth models that unconfounded measurement error from communality showed...

Classical Latent Profile Analysis of Academic Self-Concept Dimensions: Synergy of Person- and Variable-Centered Approaches to Theoretical Models of Self-Concept

Abstract: In this investigation, we used a classic latent profile analysis (LPA), a person-centered approach, to identify groups of students who had similar profiles for multiple dimensions of academic self-concept (ASC) and related these LPA groups to a diverse set of correlates. Consistent with a priori predictions, we identified 5 LPA groups representing a combination of profile level (high vs. low overall ASC) and profile shape (math vs. verbal self-concepts) that complemented results based on a traditional variable-centered approach. Whereas LPA groups were substantially and logically related to the set of 10 correlates, much of the predictive power of individual ASC factors was lost in the formation of groups and the inclusion of the correlates into the LPA distorted the nature of the groups. LPA issues examined include distinctions between quantitative (level) and qualitative (shape) differences in LPA profiles, goodness of fit and the determination of the number of LPA groups, appropriateness of correlates ...

A new look at the big five factor structure through exploratory structural equation modeling.

Abstract: NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory factor analysis (EFA), overcomes these problems with responses (N = 3,390) to the 60-item NEO-Five-Factor Inventory: (a) ESEM fits the data better and results in substantially more differentiated (less correlated) factors than does CFA; (b) tests of gender invariance with the 13-model ESEM taxonomy of full measurement invariance of factor loadings, factor variances-covariances, item uniquenesses, correlated uniquenesses, item intercepts, differential item functioning, and latent means show that women score higher on all NEO Big Five factors; (c) longitudinal analyses support measurement invariance over time and the maturity principle (decreases in Neuroticism and increases in Agreeableness, Openness, and Conscientiousness). Using ESEM, we addressed substantively important questions with broad applicability to personality research that could not be appropriately addressed with the traditional approaches of either EFA or CFA.

The Multilevel Latent Covariate Model: A New, More Reliable Approach to Group-Level Effects in Contextual Studies.

Abstract: In multilevel modeling (MLM), group-level (L2) characteristics are often measured by aggregating individual-level (L1) characteristics within each group so as to assess contextual effects (e.g., group-average effects of socioeconomic status, achievement, climate). Most previous applications have used a multilevel manifest covariate (MMC) approach, in which the observed (manifest) group mean is assumed to be perfectly reliable. This article demonstrates mathematically and with simulation results that this MMC approach can result in substantially biased estimates of contextual effects and can substantially underestimate the associated standard errors, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the sampling ratio (the percentage of cases within each group sampled), and the nature of the data. To address this pervasive problem, the authors introduce a new multilevel latent covariate (MLC) approach that corrects for unreliability at L2 and results in unbiased estimates of L2 constructs under appropriate conditions. However, under some circumstances when the sampling ratio approaches 100%, the MMC approach provides more accurate estimates. Based on 3 simulations and 2 real-data applications, the authors evaluate the MMC and MLC approaches and suggest when researchers should most appropriately use one, the other, or a combination of both approaches.

The job demands-resources model : state of the art

Abstract: Purpose – The purpose of this paper is to give a state‐of‐the art overview of the Job Demands‐Resources (JD‐R) modelDesign/methodology/approach – The strengths and weaknesses of the demand‐control model and the effort‐reward imbalance model regarding their predictive value for employee well being are discussed. The paper then introduces the more flexible JD‐R model and discusses its basic premises.Findings – The paper provides an overview of the studies that have been conducted with the JD‐R model. It discusses evidence for each of the model's main propositions. The JD‐R model can be used as a tool for human resource management. A two‐stage approach can highlight the strengths and weaknesses of individuals, work groups, departments, and organizations at large.Originality/value – This paper challenges existing stress models, and focuses on both negative and positive indicators of employee well being. In addition, it outlines how the JD‐R model can be applied to a wide range of occupations, and be used to i...

Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement

Abstract: Preface Chapter 1 The challenge Chapter 2 The nature of the evidence: A synthesis of meta-analyses Chapter 3 The argument: Visible teaching and visible learning Chapter 4: The contributions from the student Chapter 5 The contributions from the home Chapter 6 The contributions from the school Chapter 7 The contributions from the teacher Chapter 8 The contributions from the curricula Chapter 9 The contributions from teaching approaches - I Chapter 10 The contributions from teaching approaches - II Chapter 11: Bringing it all together Appendix A: The 800 meta-analyses Appendix B: The meta-analyses by rank order References

Multiple Imputation for Nonresponse in Surveys

Abstract: 25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.