Leveraging Innovative Methods in Meta-Analysis to Advance Developmental Theory

Session Type: Paper Symposium

Abstract

Our symposium highlights innovative methods in meta-analysis that can advance developmental theory. Meta-analysis is a powerful method because it affords a greater likelihood of detecting effects and identifies variability across different populations and research designs. It is also an integrative tool; meta-analysis can synthesize across domains, contexts, and time. Until recently, meta-analysis has traditionally been used to estimate associations between two variables and has primarily relied on published effects. Therefore, the extent to which meta-analyses can answer questions that advance knowledge, beyond the studies they include, has been limited.

The purpose of this symposium is to present examples of innovative methods across a diverse set of developmental questions and domains. A common theme across all presentations is the integration of familiar methods: meta-analysis and structural equation modeling (SEM). The first presentation uses individual participant data (IPD), instead of aggregate data, and multilevel modeling to compare competing models of between and within group racial/ethnic differences in the development of depressive symptoms. The second presentation applies meta-analytic SEM, which averages across correlation matrices, to examine the unique contribution of different components of executive functioning to specific writing outcomes. The third presentation also uses meta-analytic SEM to examine the direct effect of meta-linguistic skills on decoding and language comprehension, and its indirect effect on reading comprehension through decoding and language comprehension. The last presentation combines IPD and meta-analytic SEM to compare the amount of variability in depressive symptoms and academic achievement explained by components of socioeconomic status between a linear and quadratic model.

Sub Unit

• Methods, History, Theory

Chair

• Kevin Michael Korous, GDIT

Individual Presentations

• Developmental Variation in Racial/Ethnic Disparities in Depressive Symptoms: An Individual Participant Data Meta-Analysis - Presenting Author: Karina Cahill, Arizona State University; Non-Presenting Author: Kevin Michael Korous, GDIT; Non-Presenting Author: Longfeng Li, Pennsylvania State University, University Park; Non-Presenting Author: Eiko Fried, Leiden University; Non-Presenting Author: José M. Causadias, Arizona State University

• Exploring the Relations Between Executive Function and Writing Skills Across Development: A Meta-Analytic Path Analysis - Presenting Author: J. Marc Goodrich, University of Nebraska-Lincoln; Non-Presenting Author: Michael Hebert, University of Nebraska - Lincoln; Non-Presenting Author: Derek Rodgers, University of Nebraska - Lincoln; Non-Presenting Author: George Toman, University of Nebraska - Lincoln

• Simple View of Reading in Chinese: A One-stage Meta-analytic Structural Equation Modeling - Presenting Author: Peng Peng, University of Texas at Austin; Non-Presenting Author: Kejin Lee, University of Nebraska - Lincoln; Non-Presenting Author: Jie Luo, Beijing Normal University; Non-Presenting Author: Shuting Li; Non-Presenting Author: R. Malatesha Joshi, Texas A&M University; Non-Presenting Author: Sha Tao, Beijing Normal University

• Socioeconomic Status, Depressive Symptoms, and Academic Achievement: Meta-Analytic Structural Equation Modeling with Individual Participant Data - Presenting Author: Kevin Michael Korous, GDIT; Non-Presenting Author: Karina Cahill, Arizona State University; Non-Presenting Author: Longfeng Li, Pennsylvania State University, University Park; Non-Presenting Author: José M. Causadias, Arizona State University