The Cochrane Handbook for Systematic Reviews of Interventions is the official document that describes in detail the process of preparing and maintaining Cochrane systematic reviews on the effects of healthcare interventions.

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Cochrane Handbook for Systematic Reviews of Interventions

Researchers often conduct mediation analysis in order to indirectly assess the effect of a proposed cause on some outcome through a proposed mediator. The utility of mediation analysis stems from its ability to go beyond the merely descriptive to a more functional understanding of the relationships among variables. A necessary component of mediation is a statistically and practically significant indirect effect. Although mediation hypotheses are frequently explored in psychological research, formal significance tests of indirect effects are rarely conducted. After a brief overview of mediation, we argue the importance of directly testing the significance of indirect effects and provide SPSS and SAS macros that facilitate estimation of the indirect effect with a normal theory approach and a bootstrap approach to obtaining confidence intervals, as well as the traditional approach advocated by Baron and Kenny (1986). We hope that this discussion and the macros will enhance the frequency of formal mediation tests in the psychology literature. Electronic copies of these macros may be downloaded from the Psychonomic Society's Web archive at www.psychonomic.org/archive/.

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SPSS and SAS procedures for estimating indirect effects in simple mediation models.

Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.

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A new criterion for assessing discriminant validity in variance-based structural equation modeling

The unity and diversity of executive functions and their contributions to complex "Frontal Lobe" tasks: a latent variable analysis.

The following paper presents current thinking and research on fit indices for structural equation modelling. The
paper presents a selection of fit indices that are widely regarded as the most informative indices available to researchers.
As well as outlining each of these indices, guidelines are presented on their use. The paper also provides reporting
strategies of these indices and concludes with a discussion on the future of fit indices.

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Structural Equation Modelling: Guidelines for Determining Model Fit

Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation and pitfalls of structural equation modelling (SEM) in the social sciences. The book covers introductory techniques including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods such as the evaluation of non-linear effects, the analysis of means in convariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the book offers clear instructions on the preparation and screening of data, common mistakes to avoid and widely used software programs (Amos, EQS and LISREL). The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.

Principles and Practice of Structural Equation Modeling

Principles and practice of structural equation modeling, 2nd ed.

Principles and practice of structural equation modeling, 3rd ed.

Principles and practice of structural equation modeling, 4th ed.

Practices of data analysis in psychology and related disciplines are changing. This is evident in the longstanding controversy about statistical tests in the behavioral sciences and the increasing number of journals requiring effect size information. Beyond Significance Testing offers integrative and clear presentations about the limitations of statistical tests and reviews alternative methods of data analysis, such as effect size estimation (at both the group and case levels) and interval estimation (i.e., confidence intervals). Written in a clear and accessible style, the book is intended for applied researchers and students who may not have strong quantitative backgrounds. Readers will learn how to measure effect size on continuous or dichotomous outcomes in comparative studies with independent or dependent samples. They will also learn how to calculate and correctly interpret confidence intervals for effect sizes. Numerous research examples from a wide range of areas illustrate the application of these principles and how to estimate substantive significance instead of just statistical significance.

Rex B. Kline

Papers

Principles and Practice of Structural Equation Modeling

Principles and practice of structural equation modeling, 2nd ed.

Principles and practice of structural equation modeling, 3rd ed.

Principles and practice of structural equation modeling, 4th ed.

Beyond significance testing : reforming data analysis methods in behavioral research