A Review of Statistical Methods for Generalizing From Evaluations of Educational Interventions

School-based evaluations of interventions are increasingly common in education research. Ideally, the results of these evaluations are used to make evidence-based policy decisions for students. However, it is difficult to make generalizations from these evaluations because the types of schools inclu...

Full description

Saved in:
Bibliographic Details
Published inEducational Researcher Vol. 47; no. 8; pp. 516 - 524
Main Authors Tipton, Elizabeth, Olsen, Robert B.
Format Journal Article Book Review
LanguageEnglish
Published Los Angeles, CA SAGE Publishing 01.11.2018
SAGE Publications
American Educational Research Association
Subjects
Data Collection
Decision Making
Education
Educational Improvement
Educational Policy
Educational Research
Evidence Based Practice
Experimental Groups
Generalization
Guidelines
Intervention
Program Evaluation
Randomized Controlled Trials
Research design
REVIEWS/ESSAYS
Statistical Analysis
Statistical methods
generalizability
sampling
propensity scores
evaluation
educational policy
experimental research
program evaluation
multisite studies
experimental design
research methodology
external validity
policy
statistics
Online AccessGet full text

Cover

More Information
Summary:School-based evaluations of interventions are increasingly common in education research. Ideally, the results of these evaluations are used to make evidence-based policy decisions for students. However, it is difficult to make generalizations from these evaluations because the types of schools included in the studies are typically not selected randomly from a target population. This paper provides an overview of statistical methods for improving generalizations from intervention research in education. These are presented as a series of steps aimed at improving research design—particularly recruitment—as well as methods for assessing and summarizing generalizabiiity and estimating treatment impacts for clearly defined target populations.
ISSN:0013-189X
1935-102X
DOI:10.3102/0013189x18781522