Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions - Appendices

Oct 15, 2026

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Appendices for a September 2023 WWC publication examine how early literacy interventions are decomposed into component domains and analyzed using Bayesian meta-analysis. Sections describe the component coding process, implementation details across instructional practices, student supports, organizational structures, educator supports, and assessment/placement. Additional appendices provide WWC database data preparation, effect-size computation, model rationale and notation, regression covariates and priors, and further results on impact distributions and associations between specific components and intervention outcomes.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages75

Reading Time3 h 9 min

AccessFree to download

APPENDIX A. COMPONENTS OF EARLY LITERACY INTERVENTIONS

A.1 . Details of the component coding process

A.2 . Implementation of early literacy component domains

APPENDIX B. DATA FROM THE WHAT WORKS CLEARINGHOUSE’S DATABASE OF REVIEWED STUDIES

B.1 . About the WWC

B.4. Calculating effect sizes and standard errors to use in the meta-analysis

APPENDIX C. THE BAYESIAN META-ANALYTIC MODEL

C.1 . Why use a Bayesian model?

C.5 . Parameters and priors

APPENDIX D. ADDITIONAL RESULTS

D.2 . Variation in unexplained impacts of early literacy interventions

D.5 . Associations between the individual components and intervention impacts

APPENDIX E. COMPONENT CODING PROTOCOL

Coding instructions and guide for describing components of early literacy interventions

Intervention delivery

What Works Clearinghouse Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions APPENDICES A Publication of the National Center for Education Evaluation (NCEE) atIES September 2023 U.S. DEPARTMENT OF EDUCATION WWC 2023008 CONTENTS APPENDIX A. COMPONENTS OF EARLY LITERACY INTERVENTIONS....................................... 1 A.1 . Details of the component coding process .................................................................... 1 A.2 . Implementation of early literacy component domains ..................................................3 A.2.1 . Instructional practices, structures, and academic supports ................................4 A.2.2 . Non-academic student supports .....................................................................8 A.2.3 . Organizational structures and supports ...........................................................9 A.2.4. Educator supports ....................................................................................... 11 A.2.5 . Assessment and placement ...........................................................................12 APPENDIX B. DATA FROM THE WHAT WORKS CLEARINGHOUSE’S DATABASE OF REVIEWED STUDIES....................................................................................................... 14 B.1 . About the WWC......................................................................................................14 B.2 . Inclusion criteria for studies.....................................................................................14 B.3 . Preparing the WWC data for analysis.........................................................................15 B.4. Calculating effect sizes and standard errors to use in the meta-analysis..........................15 B.5 . Overview ofthe WWC study data ..............................................................................16 APPENDIX C. THE BAYESIAN META-ANALYTIC MODEL..........................................................21 C.1 . Why use a Bayesian model?......................................................................................21 C.2 . Description of the model......................................................................................... 22 C.3 . Notation ............................................................................................................... 26 C.4. Regression covariates and indexing.......................................................................... 26 C.5 . Parameters and priors ............................................................................................ 28 APPENDIX D. ADDITIONAL RESULTS ....................................................................................34 D.1 . The distribution of impacts in early literacy studies overall and by outcome type........... 34 D.2 . Variation in unexplained impacts of early literacy interventions .................................. 37 D.3 . The implementation of component domains in interventions that had positive or negative effects based on all outcome measures......................................................... 37 D.4. The extent to which the associations between component domainsand intervention impacts change when considering different outcome domains.....................................40 D.5 . Associations between the individual components and intervention impacts .................. 43 APPENDIX E. COMPONENT CODING PROTOCOL....................................................................44 Coding instructions and guide for describing components of early literacy interventions............ 44 Intervention components by type........................................................................................ 45 Component type 1: Instructional practices, structures, and supports ....................................... 47 Component type 2: Non-academic student supports .......

FAQs

What do Appendix A cover in the WWC publication?

Appendix A presents the components of early literacy interventions, including details of the component coding process and how component domains are implemented across interventions.

How does the report prepare WWC data for the meta-analysis?

Appendix B explains how reviewed study data from the WWC database are prepared, including inclusion criteria and the calculation of effect sizes and standard errors for the Bayesian meta-analysis.

What is included in Appendix C about the Bayesian meta-analytic model?

Appendix C covers the reasons for using a Bayesian model, describes the model and its notation, and specifies regression covariates, indexing, parameters, and priors.

Oct 15, 2026

Uploaded by Melati