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Wendy Chan; Jimin Oh; Chen Li; Jiexuan Huang; Yeran Tong – Society for Research on Educational Effectiveness, 2023
Background: The generalizability of a study's results continues to be at the forefront of concerns in evaluation research in education (Tipton & Olsen, 2018). Over the past decade, statisticians have developed methods, mainly based on propensity scores, to improve generalizations in the absence of random sampling (Stuart et al., 2011; Tipton,…
Descriptors: Generalizability Theory, Probability, Scores, Sampling
Afshar, Hassan Soodmand; Ranjbar, Naser – Iranian Journal of Language Teaching Research, 2023
The quality of mixing methods has been widely debated in the field of applied linguistics (AL) and the integration of data from both quantitative and qualitative research paradigms has always been open to controversy. The present study was aimed at recognizing the status quo of MMR in AL, investigating the nature of various sections of MMR…
Descriptors: Mixed Methods Research, Applied Linguistics, Research Reports, Sampling
Diego Cortes; Dirk Hastedt; Sabine Meinck – Large-scale Assessments in Education, 2025
This paper informs users of data collected in international large-scale assessments (ILSA), by presenting argumentsunderlining the importance of considering two design features employed in these studies. We examine a commonmisconception stating that the uncertainty arising from the assessment design is negligible compared with that arisingfrom the…
Descriptors: Sampling, Research Design, Educational Assessment, Statistical Inference
Yanli Xie – ProQuest LLC, 2022
The purpose of this dissertation is to develop principles and strategies for and identify limitations of multisite cluster randomized trials in the context of partially and fully nested designs. In the first study, I develop principles of estimation, sampling variability, and inference for studies that leverage multisite designs within the context…
Descriptors: Randomized Controlled Trials, Research Design, Computation, Sampling
Leslie Rutkowski; David Rutkowski – Journal of Creative Behavior, 2025
The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…
Descriptors: Creativity, Creative Thinking, Measurement, Sampling
Makela, Susanna; Si, Yajuan; Gelman, Andrew – Grantee Submission, 2018
Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to…
Descriptors: Bayesian Statistics, Statistical Inference, Sampling, Probability
Natesan, Prathiba; Hedges, Larry V. – Grantee Submission, 2016
Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in SCDs, no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3-5 observations in…
Descriptors: Bayesian Statistics, Statistical Inference, Research Design, Models
Herron, Michael C.; Quinn, Kevin M. – Sociological Methods & Research, 2016
Case studies appear prominently in political science, sociology, and other social science fields. A scholar employing a case study research design in an effort to estimate causal effects must confront the question, how should cases be selected for analysis? This question is important because the results derived from a case study research program…
Descriptors: Case Studies, Selection, Sampling, Research Design
Bennett, Kimberley Ann – Teaching Statistics: An International Journal for Teachers, 2015
Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps…
Descriptors: Statistical Analysis, Thinking Skills, Research Design, Data Interpretation
Gu, Fei; Preacher, Kristopher J.; Ferrer, Emilio – Journal of Educational and Behavioral Statistics, 2014
Mediation is a causal process that evolves over time. Thus, a study of mediation requires data collected throughout the process. However, most applications of mediation analysis use cross-sectional rather than longitudinal data. Another implicit assumption commonly made in longitudinal designs for mediation analysis is that the same mediation…
Descriptors: Statistical Analysis, Models, Research Design, Case Studies
Tipton, Elizabeth; Hedges, Larry; Vaden-Kiernan, Michael; Borman, Geoffrey; Sullivan, Kate; Caverly, Sarah – Journal of Research on Educational Effectiveness, 2014
Randomized experiments are often seen as the "gold standard" for causal research. Despite the fact that experiments use random assignment to treatment conditions, units are seldom selected into the experiment using probability sampling. Very little research on experimental design has focused on how to make generalizations to well-defined…
Descriptors: Probability, Inferences, Eligibility, Recruitment
Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric – Journal of Experimental Education, 2015
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…
Descriptors: Effect Size, Measurement Techniques, Statistical Analysis, Research Design
Ugille, Maaike; Moeyaert, Mariola; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2014
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…
Descriptors: Effect Size, Statistical Bias, Sample Size, Regression (Statistics)
Collins, Kathleen M. T.; Onwuegbuzie, Anthony J. – New Directions for Evaluation, 2013
The goal of this chapter is to recommend quality criteria to guide evaluators' selections of sampling designs when mixing approaches. First, we contextualize our discussion of quality criteria and sampling designs by discussing the concept of interpretive consistency and how it impacts sampling decisions. Embedded in this discussion are…
Descriptors: Sampling, Mixed Methods Research, Evaluators, Q Methodology
Harvill, Eleanor L.; Peck, Laura R.; Bell, Stephen H. – American Journal of Evaluation, 2013
Using exogenous characteristics to identify endogenous subgroups, the approach discussed in this method note creates symmetric subsets within treatment and control groups, allowing the analysis to take advantage of an experimental design. In order to maintain treatment--control symmetry, however, prior work has posited that it is necessary to use…
Descriptors: Experimental Groups, Control Groups, Research Design, Sampling
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