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Dahlia K. Remler; Gregg G. Van Ryzin – American Journal of Evaluation, 2025
This article reviews the origins and use of the terms quasi-experiment and natural experiment. It demonstrates how the terms conflate whether variation in the independent variable of interest falls short of random with whether researchers find, rather than intervene to create, that variation. Using the lens of assignment--the process driving…
Descriptors: Quasiexperimental Design, Research Design, Experiments, Predictor Variables
Zuchao Shen; Ben Kelcey – Society for Research on Educational Effectiveness, 2023
I. Purpose of the Study: Detecting whether interventions work or not (through main effect analysis) can provide empirical evidence regarding the causal linkage between malleable factors (e.g., interventions) and learner outcomes. In complement, moderation analyses help delineate for whom and under what conditions intervention effects are most…
Descriptors: Intervention, Program Effectiveness, Evidence, Research Design
Eric C. Hedberg – Grantee Submission, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
E. C. Hedberg – American Journal of Evaluation, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
Xinran Li; Peng Ding; Donald B. Rubin – Grantee Submission, 2020
With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Therefore, it is intuitive to restrict the randomization of the treatment factors to satisfy certain covariate balance criteria, possibly conforming to the tiers of…
Descriptors: Experiments, Research Design, Randomized Controlled Trials, Sampling
Wu, Edward; Gagnon-Bartsch, Johann A. – Journal of Educational and Behavioral Statistics, 2021
In paired experiments, participants are grouped into pairs with similar characteristics, and one observation from each pair is randomly assigned to treatment. The resulting treatment and control groups should be well-balanced; however, there may still be small chance imbalances. Building on work for completely randomized experiments, we propose a…
Descriptors: Experiments, Groups, Research Design, Statistical Analysis
Benjamin A. Motz; Öykü Üner; Harmony E. Jankowski; Marcus A. Christie; Kim Burgas; Diego del Blanco Orobitg; Mark A. McDaniel – Grantee Submission, 2023
For researchers seeking to improve education, a common goal is to identify teaching practices that have causal benefits in classroom settings. To test whether an instructional practice exerts a causal influence on an outcome measure, the most straightforward and compelling method is to conduct an experiment. While experimentation is common in…
Descriptors: Learning Analytics, Experiments, Learning Processes, Learning Management Systems
Westlund, Erik; Stuart, Elizabeth A. – American Journal of Evaluation, 2017
This article discusses the nonuse, misuse, and proper use of pilot studies in experimental evaluation research. The authors first show that there is little theoretical, practical, or empirical guidance available to researchers who seek to incorporate pilot studies into experimental evaluation research designs. The authors then discuss how pilot…
Descriptors: Use Studies, Pilot Projects, Evaluation Research, Experiments
Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models