Advances in Meta-Analysis
By Terri D. Pigott. 2012
326 citations recorded by the source corpus.
Subfields: Education, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/dd58d1c0b728b0aed1c73559f054ee328cc78559
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Education
- Eugene F. Borokhovski
- Philip C. Abrami
- Rana M. Tamim
- Robert M. Bernard
- J. Polanin
- Richard F. Schmid
- Ulf Böckenholt
- Blakeley B. McShane
In Statistics and Probability
- Blakeley B. McShane
- Ulf Böckenholt
- J. Polanin
- Terri D. Pigott
- Mike W.-L. Cheung
- Frank Fischer
- M. Bühner
- Matthias Schwaighofer
Citations in the corpus
- Working Memory Training Does Not Improve Performance on Measures of Intelligence or Other Measures of “Far Transfer”: Evidence from a Meta-Analytic Review (2016, unknown): “Moderators are variables that may explain why different studies show different results (Pigott, 2012).”
- The effects of technology use in postsecondary education: A meta-analysis of classroom applications (2014, methodology): “For the purposes of meta-analysis, R 2 is incorrect and cannot be interpreted (Pigott, 2012).”
- Large-Scale Replication Projects in Contemporary Psychological Research (2017, background): “More systematically, Simons et al. (2017) make the excellent suggestion that all primary research papers include a “Constraints on Generality” statement that identifies key method factors, thereby “help[ing] other researchers.”
- Mathematics Interventions for Upper Elementary and Secondary Students: A Meta-Analysis of Research (2018, unknown): “To quantify intervention effects, we calculated the standardized mean difference and corrected for small-sample size bias using Hedge’s g (Pigott, 2012).”
- A Systematic Review of Personality Trait Change Through Intervention (2017, unknown): “First, between-study variance reduces statistical power (Pigott, 2012).”
- Single Paper Meta-Analysis: Benefits For Study Summary, Theory-Testing, and Replicability (2017, methodology): “…Fabrigar and Wegener 2016; Rosenthal 1991; Stroebe and Strack 2014; Tsang and Kwan 1999), our SPM methodology estimates and accounts for heterogeneity, which has been shown to be important in a wide variety of behavioral research settings (Hedges and Pigott 2001; Klein et al. 2014; Pigott 2012).”
- The effect of exposure to sexual appeals in advertisements on memory, attitude, and purchase intention: a meta-analytic review (2018, methodology): “A relevant option here is a meta-analysis, as meta-analyses allow researchers to combine results from a sample of studies in order to test whether an average effect size differs significantly from zero (Lipsey and Wilson 2001; Pigott 2012).”
- Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review (2019, background): “Recent decades have seen an increase in the use of meta-analysis (Williams, 2012), availability of approachable meta-analytic software (Polanin, Hennessey, & Tanner-Smith, 20171), and multiple methodological developments (Pigott, 2012).”
- Adjusting for Publication Bias in Meta-Analysis (2016, methodology): “Thus, according to the taxonomy of Pigott (2012), this is a medium amount of heterogeneity (she defines low heterogeneity as I2 = 25%, medium heterogeneity as I2 = 50%, and high heterogeneity as I2 = 75%).”
- Best practice guidelines for abstract screening large‐evidence systematic reviews and meta‐analyses (2019, background): “Conducting a systematic review and meta‐analysis, large or small, requires dedicated planning, consistent information tracking, and constant managerial oversight.(1) A high‐quality review relies on a team of content and methodological members' expertise combined with knowledge”
- Treatment for School Refusal Among Children and Adolescents (2018, unknown): “We used the standardized-mean difference effect size statistic, correcting for small-sample bias using Hedges’ g (Pigott, 2012).”
- The Effects of Home Literacy Environment on Children’s Reading Comprehension Development: A Meta-analysis (2020, background): “The point estimation was regarded to be significant if the 95% confidence interval (95% CI) did not cross zero (Pigott, 2012).”
- STEMulating Interest: A Meta-Analysis of the Effects of Out-of-School Time on Student STEM Interest (2016, background): “According to Pigott (2012), a random effects moderator analysis is best suited for investigations of multiple sources of variation amongst studies that can be accounted for by study characteristics.”
- Bullying and Suicidal Ideation and Behaviors: A Meta-Analysis (2015, unknown): “74) Series of behavioral questions 12 (26) 2.”