An Individual Participant Data Meta-Analysis to Support Power Analyses for Randomized Intervention Studies in Preschool: Cognitive and Socio-Emotional Learning Outcomes
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| Title: | An Individual Participant Data Meta-Analysis to Support Power Analyses for Randomized Intervention Studies in Preschool: Cognitive and Socio-Emotional Learning Outcomes |
|---|---|
| Language: | English |
| Authors: | Martin Brunner (ORCID |
| Source: | Educational Psychology Review. 2025 37. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 38 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Information Analyses |
| Education Level: | Early Childhood Education Preschool Education |
| Descriptors: | Preschools, Social Emotional Learning, Outcomes of Education, Cognitive Objectives, Child Care Centers, Foreign Countries, Preschool Children, Child Development, Journal Articles, Statistical Analysis, Early Childhood Education, Educational Research, Randomized Controlled Trials |
| Geographic Terms: | Germany |
| DOI: | 10.1007/s10648-024-09981-z |
| ISSN: | 1040-726X 1573-336X |
| Abstract: | There is a need for robust evidence about which educational interventions work in preschool to foster children's cognitive and socio-emotional learning (SEL) outcomes. Lab-based individually randomized experiments can develop and refine such interventions, and field-based randomized experiments (e.g., cluster randomized trials) evaluate their effectiveness in real-world daycare center settings. Applying reliable estimates of design parameters in the context of a priori power analyses is essential to ensure that the sample size of these studies is adequate to support strong statistical conclusions regarding the strength of the intervention effect. However, there is little knowledge on relevant design parameters with preschool children. We therefore utilized a systematic collection of individual participant data from four German probability samples (554 [less than or equal to] N [less than or equal to] 2928) with preschool children (aged two to six years) to estimate and meta-analyze design parameters. These parameters are relevant for planning single-level (e.g., in non-clustered lab-based settings), two-level (children nested in daycare centers), and three-level (children nested in groups, with groups nested in daycare centers) randomized intervention studies targeting cognitive and SEL outcomes assessed with three methods (standardized tests, parent ratings, and educator ratings). The design parameters depict between-group and -center differences as well as the proportion of variance in the outcomes explained by different covariate sets (socio-demographic characteristics, baseline measures, and their combination) at the child, group, and center level. In conclusion, this paper provides a rich source of design parameters, recommendations, and illustrations to support a priori power analyses for randomized intervention studies in early childhood education research. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1457332 |
| Database: | ERIC |
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| Abstract: | There is a need for robust evidence about which educational interventions work in preschool to foster children's cognitive and socio-emotional learning (SEL) outcomes. Lab-based individually randomized experiments can develop and refine such interventions, and field-based randomized experiments (e.g., cluster randomized trials) evaluate their effectiveness in real-world daycare center settings. Applying reliable estimates of design parameters in the context of a priori power analyses is essential to ensure that the sample size of these studies is adequate to support strong statistical conclusions regarding the strength of the intervention effect. However, there is little knowledge on relevant design parameters with preschool children. We therefore utilized a systematic collection of individual participant data from four German probability samples (554 [less than or equal to] N [less than or equal to] 2928) with preschool children (aged two to six years) to estimate and meta-analyze design parameters. These parameters are relevant for planning single-level (e.g., in non-clustered lab-based settings), two-level (children nested in daycare centers), and three-level (children nested in groups, with groups nested in daycare centers) randomized intervention studies targeting cognitive and SEL outcomes assessed with three methods (standardized tests, parent ratings, and educator ratings). The design parameters depict between-group and -center differences as well as the proportion of variance in the outcomes explained by different covariate sets (socio-demographic characteristics, baseline measures, and their combination) at the child, group, and center level. In conclusion, this paper provides a rich source of design parameters, recommendations, and illustrations to support a priori power analyses for randomized intervention studies in early childhood education research. |
|---|---|
| ISSN: | 1040-726X 1573-336X |
| DOI: | 10.1007/s10648-024-09981-z |
