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We present the R package and web app statcheck to automatically detect statistical reporting inconsistencies in primary studies and meta‐analyses. Previous research has shown a high prevalence of reported p‐values that are inconsistent ‐ meaning a re‐calculated p‐value, based on the reported test statistic and degrees of freedom, does not match the author‐reported p‐value. Such inconsistencies affect the reproducibility and evidential value of published findings. The tool statcheck can help researchers to identify statistical inconsistencies so that they may correct them. In this paper, we provide an overview of the prevalence and consequences of statistical reporting inconsistencies. We also discuss the tool statcheck in more detail and give an example of how it can be used in a meta‐analysis. We end with some recommendations concerning the use of statcheck in meta‐analyses and make a case for better reporting standards of statistical results. [ABSTRACT FROM AUTHOR]

Abstract screening is one important aspect of conducting a high‐quality and comprehensive systematic review and meta‐analysis. Abstract screening allows the review team to conduct the tedious but vital first step to synthesize the extant literature: winnowing down the overwhelming amalgamation of citations discovered through research databases to the citations that should be "full‐text" screened and eventually included in the review. Although it is a critical process, few guidelines have been put forth since the publications of seminal systematic review textbooks. The purpose of this paper, therefore, is to provide a practical set of best practice guidelines to help future review teams and managers. Each of the 10 proposed guidelines is explained using real‐world examples or illustrations from applications. We also delineate recent experiences where a team of abstract screeners double‐screened 14 923 abstracts in 89 days. [ABSTRACT FROM AUTHOR]

Individual participant data (IPD) is the backbone of scientific inquiry and important to a meta-analysis for a variety of reasons. It is therefore important to be able to access IPD, and yet, obstacles persist that make it difficult for meta-analysts, as well as interested primary study analysts, to obtain it. In this paper, we discuss the barriers to obtaining IPD via online repositories or contacting primary study authors and provide an example data sharing agreement that can be used to ameliorate a few of these issues. We also discuss the ethics of data sharing. The goal of this paper is to help meta-analysts anticipate these potential barriers at the outset of their studies and hopefully increase the likelihood of producing thorough IPD syntheses and foster collaborative partnerships with primary study researchers. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation coefficients that exhibit substantial heterogeneity, some of which obscures the relationships between the constructs of interest or undermines the comparability of the correlations across the cells. One component of this approach is a three-level random effects model capable of synthesizing a pooled correlation matrix with dependent correlation coefficients. Another component is a meta-regression that can be used to generate covariate-adjusted correlation coefficients that reduce the influence of selected unevenly distributed moderator variables. A non-technical presentation of these techniques is given, along with an illustration of the procedures with a meta-analytic dataset. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Parenting self-efficacy (PSE) includes parents' self-perceptions regarding their capabilities in performing the numerous and changing tasks associated with parenting a specific child (i.e., domain-specific PSE) as well as their self-perceptions in the parenting role overall (i.e., domain-general PSE). Prior literature has demonstrated PSE's relations with numerous constructs significant to mental health and the parent-infant relationship. Prior measures of PSE have been limited by focusing on only domain-specific or domain-general PSE, ignoring the importance of infant development to PSE, and other psychometric limitations. This article presents sound psychometric data for a new measure of PSE, the Assessment of Parenting Tool (APT). The APT includes task-level items on the Domain-Specific subscale (APT-DS) for each age-referenced version of the measure as well as a domain-general subscale that taps overall PSE within the first 24 months' postpartum. Initial construct validity of the measure is established, particularly for parents of infants aged 3 months and older. A stable, three-factor structure for the domain-general subscale includes 'coping with being a parent,' 'attuned parenting,' and 'self-perceived model parenting.' Future directions for the APT, including a revised checklist format for the domain-specific subscale, are included. [ABSTRACT FROM AUTHOR]

Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one review, is an underdeveloped literature. We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how meta-analysts should analyze multiple tests of statistical significance. The context for this study is a meta-review of meta-analyses published in two leading review journals in education and psychology. Our review of 130 meta-analyses revealed a strong reliance on statistical significance testing without consideration of Type I errors or the use of multiplicity corrections. In order to provide valid conclusions, meta-analysts must consider these issues prior to conducting the review. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The purpose of this study is to (a) validate the psychometric properties of the Perceived Employment Barrier Scale (PEBS) and (b) investigate the effect of perceived barriers on employment hope. An exploratory factor analysis (EFA), a confirmatory factor analysis (CFA), and a series of invariance tests were conducted to validate PEBS using two independent samples. Structural equation modeling (SEM) was used to test the hypothesized relationship. The latent factor structure generated by EFA failing to fit efficiently in CFA, the model was revised to a 5-factor, 20-item structure. This model demonstrated a common latent factor and item structure in both samples. And SEM results suggest a significant negative effect of perceived employment barriers on employment hope. PEBS is a reliable and valid measure that could be used as an evidence-based tool for comprehensively assessing client-centered employment barriers and providing appropriate support services to low-income jobseekers. [ABSTRACT FROM AUTHOR]

The current study examined the extent to which college women in science, technology, engineering, and math (STEM) majors demonstrated differential levels of leadership capacity and/or leader efficacy than their non-STEM, female peers. Data represented 14,698 women from 86 institutions of higher education in the United States. Results indicated similar levels of leadership capacity but significantly lower leader efficacy for women in STEM majors. Implications explore unique predictors of leader efficacy for women in STEM majors along with recommendations for changes to policy and professional practice that might address how the differential organizational contexts shape leadership development. [ABSTRACT FROM AUTHOR]