In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of measurement models using confirmatory factor analysis are reviewed. As background to the two-step approach, the distinction between exploratory and confirmatory analysis, the distinction between complementary approaches for theory testing versus predictive application, and some developments in estimation methods also are discussed.

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Structural equation modeling in practice: a review and recommended two-step approach

Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.

Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.

The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-3j53e5oe33.pdf

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

Part One: The Context Of Educational Research Part Two: Planning Educational Research Part Three: Styles Of Educational Research Part Four: Strategies And Instruments For Data Collection And Researching Part Five: Data Analysis

Research Methods in Education

During the past 30 years, meta-analysis has been an indispensable tool for revealing the hidden meaning of our research literatures. The four articles in this special section on meta-analysis illus...

Meta-Analysis: A Constantly Evolving Research Integration Tool

Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-48ibbzju0k.pdf

The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

(1983). Problems in Measuring the Quality of Investment Information: The Perils of the Information Coefficient. Financial Analysts Journal: Vol. 39, No. 3, pp. 25-33.

Problems in Measuring the Quality of Investment Information: The Perils of the Information Coefficient

Literature reviewers have drawn dramatically different conclusions about the effectiveness of management by objectives (MBO). Some reviewers drew quite optimistic conclusions about the value of MBO...

The Discard of Study Evidence by Literature Reviewers

A potential source of confusion in the interpretation of a LISREL-IV analysis is the metric of the latent variables. This paper demonstrates that fixing the pattern coefficient of one of the indicators of each latent variable to 1.0 results in an arbitrary and meaningless metric which is usually different for each latent variable. Since many of the parameter estimates such as the pattern coefficients, the factor loadings, and the variance-covariance matrix of the latent variables are a function of the metric of the latent variables, much of the LISREL-IV output may be uninterpretable. This paper demonstrates how to specify a priori the variances of the latent variables in a LISREL-IV analysis.

The Metric of the Latent Variables in a LISREL-IV Analysis

Personality differences between randomly selected migrainous and non-migrainous people.

Murphy and Myors (this issue) challenge the conclusion by Schmidt (1991) that banding procedures in personnel selection are fatally flawed logically. In this article, we show that their challenge is based on a misunderstanding of the nature of Schmidt's argument. We show that when that argument is properly understood, it does in fact require the conclusion that there is a fatal logical inconsistency between the statistical rationale underlying banding and the operational procedures for banding. The first part of this article demonstrates this for banding in general; the second part elucidates this inconsistency for a particular form of banding that is currently quite popular-the sliding band with minority preference. We show that the comparisons drawn by Murphy and Myors between banding and scoring procedures such as stanine scores and college grades are based on their misunderstanding of the Schmidt argument and are therefore conceptually and mathematically inappropriate and irrelevant.

John E. Hunter

Papers

Problems in Measuring the Quality of Investment Information: The Perils of the Information Coefficient

The Discard of Study Evidence by Literature Reviewers

The Metric of the Latent Variables in a LISREL-IV Analysis

Personality differences between randomly selected migrainous and non-migrainous people.

The Fatal Internal Contradiction in Banding: Its Statistical Rationale is Logically Inconsistent With Its Operational Procedures