Diana Adler

Bio: Diana Adler is an academic researcher. The author has contributed to research in topics: Data matrix (multivariate statistics) & Multivariate statistics. The author has an hindex of 1, co-authored 1 publications receiving 11850 citations.

Using Multivariate Statistics

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The New Statistics Why and How

Abstract: We need to make substantial changes to how we conduct research. First, in response to heightened concern that our published research literature is incomplete and untrustworthy, we need new requirements to ensure research integrity. These include prespecification of studies whenever possible, avoidance of selection and other inappropriate data- analytic practices, complete reporting, and encouragement of replication. Second, in response to renewed recognition of the severe flaws of null-hypothesis significance testing (NHST), we need to shift from reliance on NHST to estimation and other preferred techniques. The new statistics refers to recommended practices, including estimation based on effect sizes, confidence intervals, and meta-analysis. The techniques are not new, but adopting them widely would be new for many researchers, as well as highly beneficial. This article explains why the new statistics are important and offers guidance for their use. It describes an eight-step new-statistics strategy for research with integrity, which starts with formulation of research questions in estimation terms, has no place for NHST, and is aimed at building a cumulative quantitative discipline.

Gender differences in scholastic achievement: a meta-analysis.

Abstract: A female advantage in school marks is a common finding in education research, and it extends to most course subjects (e.g., language, math, science), unlike what is found on achievement tests. However, questions remain concerning the quantification of these gender differences and the identification of relevant moderator variables. The present meta-analysis answered these questions by examining studies that included an evaluation of gender differences in teacher-assigned school marks in elementary, junior/middle, or high school or at the university level (both undergraduate and graduate). The final analysis was based on 502 effect sizes drawn from 369 samples. A multilevel approach to meta-analysis was used to handle the presence of nonindependent effect sizes in the overall sample. This method was complemented with an examination of results in separate subject matters with a mixed-effects metaanalytic model. A small but significant female advantage (mean d 0.225, 95% CI [0.201, 0.249]) was demonstrated for the overall sample of effect sizes. Noteworthy findings were that the female advantage was largest for language courses (mean d 0.374, 95% CI [0.316, 0.432]) and smallest for math courses (mean d 0.069, 95% CI [0.014, 0.124]). Source of marks, nationality, racial composition of samples, and gender composition of samples were significant moderators of effect sizes. Finally, results showed that the magnitude of the female advantage was not affected by year of publication, thereby contradicting claims of a recent “boy crisis” in school achievement. The present meta-analysis demonstrated the presence of a stable female advantage in school marks while also identifying critical moderators. Implications for future educational and psychological research are discussed.

A Meta-Analysis of the Efficacy of Acceptance and Commitment Therapy for Clinically Relevant Mental and Physical Health Problems

Abstract: Background: The current study presents the results of a meta-analysis of 39 randomized controlled trials on the efficacy of acceptance and commitment therapy (ACT), including 1,821 patients with mental disorders or somatic health problems. Methods: We searched PsycINFO, MEDLINE and the Cochrane Central Register of Controlled Trials. Information provided by the ACBS (Association of Contextual Behavioral Science) community was also included. Statistical calculations were conducted using Comprehensive Meta-Analysis software. Study quality was rated using a methodology rating form. Results: ACT outperformed control conditions (Hedges' g = 0.57) at posttreatment and follow-up assessments in completer and intent-to-treat analyses for primary outcomes. ACT was superior to waitlist (Hedges' g = 0.82), to psychological placebo (Hedges' g = 0.51) and to treatment as usual (TAU) (we defined TAU as the standard treatment as usual; Hedges' g = 0.64). ACT was also superior on secondary outcomes (Hedges' g = 0.30), life satisfaction/quality measures (Hedges' g = 0.37) and process measures (Hedges' g = 0. 56) compared to control conditions. The comparison between ACT and established treatments (cognitive behavioral therapy) did not reveal any significant differences between these treatments (p = 0.140). Conclusions: Our findings indicate that ACT is more effective than treatment as usual or placebo and that ACT may be as effective in treating anxiety disorders, depression, addiction, and somatic health problems as established psychological interventions. More research that focuses on quality of life and processes of change is needed to understand the added value of ACT and its transdiagnostic nature.