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Petersen, Ashley – Journal of Statistics and Data Science Education, 2022
While correlated data methods (like random effect models and generalized estimating equations) are commonly applied in practice, students may struggle with understanding the reasons that standard regression techniques fail if applied to correlated outcomes. To this end, this article presents an in-class activity using results from Monte Carlo…
Descriptors: Intuition, Skill Development, Correlation, Graduate Students
Huang, Francis L. – Journal of Experimental Education, 2022
Experiments in psychology or education often use logistic regression models (LRMs) when analyzing binary outcomes. However, a challenge with LRMs is that results are generally difficult to understand. We present alternatives to LRMs in the analysis of experiments and discuss the linear probability model, the log-binomial model, and the modified…
Descriptors: Regression (Statistics), Monte Carlo Methods, Probability, Error Patterns
Corinne Huggins-Manley; Anthony W. Raborn; Peggy K. Jones; Ted Myers – Journal of Educational Measurement, 2024
The purpose of this study is to develop a nonparametric DIF method that (a) compares focal groups directly to the composite group that will be used to develop the reported test score scale, and (b) allows practitioners to explore for DIF related to focal groups stemming from multicategorical variables that constitute a small proportion of the…
Descriptors: Nonparametric Statistics, Test Bias, Scores, Statistical Significance
Koziol, Natalie A. – Applied Measurement in Education, 2016
Testlets, or groups of related items, are commonly included in educational assessments due to their many logistical and conceptual advantages. Despite their advantages, testlets introduce complications into the theory and practice of educational measurement. Responses to items within a testlet tend to be correlated even after controlling for…
Descriptors: Classification, Accuracy, Comparative Analysis, Models
Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand – International Journal of Mathematical Education in Science and Technology, 2017
The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…
Descriptors: Calculus, Probability, Data Analysis, Computation
Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups
Wu, Meng-Jia; Becker, Betsy Jane – Research Synthesis Methods, 2013
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…
Descriptors: Regression (Statistics), Correlation, Research Methodology, Accuracy
Chipere, Ngoni – International Journal on E-Learning, 2015
The objectives of the study were to identify best practices in online doctoral programming and to synthesise these practices into a framework for developing online doctoral programmes. The field of online doctoral studies is nascent and presents challenges for conventional forms of literature review. The literature was therefore reviewed using a…
Descriptors: Foreign Countries, Best Practices, Online Courses, Electronic Learning
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
Dong, Nianbo – American Journal of Evaluation, 2015
Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…
Descriptors: Probability, Statistical Analysis, Research Design, Causal Models
Yuan, Ke-Hai; Chan, Wai – Psychometrika, 2011
The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…
Descriptors: Statistical Bias, Error of Measurement, Regression (Statistics), Predictor Variables
Qian, Xiaoyu; Nandakumar, Ratna; Glutting, Joseoph; Ford, Danielle; Fifield, Steve – ETS Research Report Series, 2017
In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…
Descriptors: Item Analysis, Gender Differences, Achievement Gap, Grade 8
Grissmer, David W.; Ober, David R.; Beekman, John A. – Education Policy Analysis Archives, 2014
The short-term emphasis engendered by No Child Left Behind (NCLB) has focused research predominantly on unraveling the complexities and uncertainties in assessing short-term results, rather than developing methods and assessing results over the longer term. In this paper we focus on estimating long-term gains and address questions important to…
Descriptors: Educational Assessment, Achievement Gains, Federal Legislation, Educational Legislation
Peer reviewedMaeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics
Peer reviewedChan, Wai; Yung, Yiu-Fai; Bentler, Peter M.; Tang, Man-Lai – Educational and Psychological Measurement, 1998
Two bootstrap tests are proposed to test the independence hypothesis in a two-way cross table. Monte Carlo studies are used to compare the traditional asymptotic test with these bootstrap methods, and the bootstrap methods are found superior in two ways: control of Type I error and statistical power. (SLD)
Descriptors: Hypothesis Testing, Monte Carlo Methods, Power (Statistics), Predictor Variables
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