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Ting Ye; Ted Westling; Lindsay Page; Luke Keele – Grantee Submission, 2024
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…
Descriptors: Nonparametric Statistics, Identification, Causal Models, Multivariate Analysis
Beechey, Timothy – Journal of Speech, Language, and Hearing Research, 2023
Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…
Descriptors: Hypothesis Testing, Multivariate Analysis, Data Analysis, Statistical Inference
Yuqi Gu; Elena A. Erosheva; Gongjun Xu; David B. Dunson – Grantee Submission, 2023
Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying,…
Descriptors: Multivariate Analysis, Item Response Theory, Bayesian Statistics, Models
Schweig, Jonathan David; Pane, John F. – International Journal of Research & Method in Education, 2016
Demands for scientific knowledge of what works in educational policy and practice has driven interest in quantitative investigations of educational outcomes, and randomized controlled trials (RCTs) have proliferated under these conditions. In educational settings, even when individuals are randomized, both experimental and control students are…
Descriptors: Randomized Controlled Trials, Educational Research, Multivariate Analysis, Models
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
Pampaka, Maria; Hutcheson, Graeme; Williams, Julian – International Journal of Research & Method in Education, 2016
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Sang, Jane – Journal of Education and Practice, 2016
The purpose of this study to assess communication channels as implementation determinants of performance management framework In Kenya at Moi Teaching and Referral Hospital (MTRH). The communication theory was used to inform the study. This study adopted an explanatory design. The target sampled 510 respondents through simple random and stratified…
Descriptors: Foreign Countries, Program Implementation, Models, Multivariate Analysis
Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D. – International Journal of Behavioral Development, 2014
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This article explores this question by using…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Huo, Yan; Budescu, David V. – Multivariate Behavioral Research, 2009
Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…
Descriptors: Multivariate Analysis, Correlation, Regression (Statistics), Models
Bajgier, Steve M.; Atkinson, MaryAnne – Collegiate Microcomputer, 1989
Describes the use of a simulated learning environment (SLE) as an instructional aid in teaching multivariate statistics, particularly inferential statistics. A prototype microcomputer-based SLE called MVWORLD developed at Drexel University for upper level statistics courses is explained, and implementing a statistics laboratory for multivariate…
Descriptors: Computer Assisted Instruction, Computer Simulation, Courseware, Educational Environment