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Fangxing Bai; Ben Kelcey; Yanli Xie; Kyle Cox – Journal of Experimental Education, 2025
Prior research has suggested that clustered regression discontinuity designs are a formidable alternative to cluster randomized designs because they provide targeted treatment assignment while maintaining a high-quality basis for inferences on local treatment effects. However, methods for the design and analysis of clustered regression…
Descriptors: Regression (Statistics), Statistical Analysis, Research Design, Educational Research
Olsson, Ulf – Practical Assessment, Research & Evaluation, 2022
We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated,…
Descriptors: Regression (Statistics), Likert Scales, Sampling, Nonparametric Statistics
Bulus, Metin – ProQuest LLC, 2017
In education, sample characteristics can be complex due to the nested structure of students, teachers, classrooms, schools, and districts. In the past, not many considerations were given to such complex sampling schemes in statistical power analysis. More recently in the past two decades, however, education scholars have developed tools to conduct…
Descriptors: Educational Research, Regression (Statistics), Research Design, Statistical Analysis
Finch, William Holmes; Hernandez Finch, Maria E. – AERA Online Paper Repository, 2017
High dimensional multivariate data, where the number of variables approaches or exceeds the sample size, is an increasingly common occurrence for social scientists. Several tools exist for dealing with such data in the context of univariate regression, including regularization methods such as Lasso, Elastic net, Ridge Regression, as well as the…
Descriptors: Multivariate Analysis, Regression (Statistics), Sampling, Sample Size
Beaujean, A. Alexander – Practical Assessment, Research & Evaluation, 2014
A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…
Descriptors: Regression (Statistics), Sample Size, Sampling, Monte Carlo Methods
Tipton, Elizabeth; Pustejovsky, James E. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Descriptors: Randomized Controlled Trials, Sample Size, Effect Size, Hypothesis Testing
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)
Huang, Francis L. – Practical Assessment, Research & Evaluation, 2014
Clustered data (e.g., students within schools) are often analyzed in educational research where data are naturally nested. As a consequence, multilevel modeling (MLM) has commonly been used to study the contextual or group-level (e.g., school) effects on individual outcomes. The current study investigates the use of an alternative procedure to…
Descriptors: Hierarchical Linear Modeling, Regression (Statistics), Educational Research, Sampling
Sabina, Asiago Lenah; Okibo, Walter; Nyang'au, Andrew; Ondima, Cleophas – Journal of Education and Practice, 2015
Job satisfaction is a major challenge among employees in many organizations. The purpose of this research project is to assess the effect of non-financial incentives on job satisfaction of teachers in public secondary schools of Kisii Sub County in the Republic of Kenya. The specific objectives for the study include: to assess the effect of…
Descriptors: Foreign Countries, Job Satisfaction, Secondary School Teachers, Regression (Statistics)
Lai, Mark H. C.; Kwok, Oi-man – Journal of Experimental Education, 2015
Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…
Descriptors: Educational Research, Research Design, Cluster Grouping, Statistical Data
Yagiz, Oktay; Aydin, Burcu; Akdemir, Ahmet Selçuk – Journal of Language and Linguistic Studies, 2016
This study reviews a selected sample of 274 research articles on ELT, published between 2005 and 2015 in Turkish contexts. In the study, 15 journals in ULAKBIM database and articles from national and international journals accessed according to convenience sampling method were surveyed and relevant articles were obtained. A content analysis was…
Descriptors: Journal Articles, Periodicals, Content Analysis, Research Design
Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2011
Large surveys often use probability sampling in order to obtain representative samples, and these data sets are valuable tools for researchers in all areas of science. Yet many researchers are not formally prepared to appropriately utilize these resources. Indeed, users of one popular dataset were generally found "not" to have modeled…
Descriptors: Best Practices, Sampling, Sample Size, Data Analysis
Puhan, Gautam – International Journal of Testing, 2011
This study examined the effect of including or excluding repeaters on the equating process and results. New forms of two tests were equated to their respective old forms using either all examinees or only the first timer examinees in the new form sample. Results showed that for both tests used in this study, including or excluding repeaters in the…
Descriptors: Equated Scores, Educational Testing, Student Evaluation, Sample Size
Moerbeek, Mirjam – Journal of Educational and Behavioral Statistics, 2008
Three issues need to be decided in the design stage of a longitudinal intervention study: the number of persons, the number of repeated measurements per person, and the duration of the study. The degree to which polynomial effects vary across persons and the drop-out pattern also influence the statistical power to detect intervention effects. This…
Descriptors: Intervention, Sample Size, Research Methodology, Longitudinal Studies
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2008
This article examines theoretical and empirical issues related to the statistical power of impact estimates for experimental evaluations of education programs. The author considers designs where random assignment is conducted at the school, classroom, or student level, and employs a unified analytic framework using statistical methods from the…
Descriptors: Elementary School Students, Research Design, Standardized Tests, Program Evaluation
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