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Erin W. Post – ProQuest LLC, 2024
Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…
Descriptors: Regression (Statistics), Multivariate Analysis, Statistical Distributions, Bayesian Statistics
Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Descriptors: Error of Measurement, Monte Carlo Methods, Data Collection, Simulation
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Tutz, Gerhard; Berger, Moritz – Journal of Educational and Behavioral Statistics, 2016
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…
Descriptors: Response Style (Tests), Rating Scales, Data Interpretation, Statistical Bias
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Gaševic, Dragan; Jovanovic, Jelena; Pardo, Abelardo; Dawson, Shane – Journal of Learning Analytics, 2017
The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper…
Descriptors: Foreign Countries, Undergraduate Students, Engineering Education, Educational Research
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Irby, Stefan M.; Phu, Andy L.; Borda, Emily J.; Haskell, Todd R.; Steed, Nicole; Meyer, Zachary – Chemistry Education Research and Practice, 2016
There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…
Descriptors: Chemistry, Formative Evaluation, Graduate Students, College Students
Baydogan, Mustafa Gokce – ProQuest LLC, 2012
Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…
Descriptors: Mathematical Models, Multivariate Analysis, Statistical Data, Computation
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Skelly, JoAnne; Hill, George; Singletary, Loretta – Journal of Extension, 2014
Extension professionals often assess community needs to determine programs and target audiences. Data can be collected through surveys, focus group and individual interviews, meta-analysis, systematic observation, and other methods. Knowledge gaps are identified, and programs are designed to resolve the deficiencies. However, do Extension…
Descriptors: Needs Assessment, Data Analysis, Community Needs, Extension Education
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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
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Nimon, Kim; Henson, Robin K.; Gates, Michael S. – Multivariate Behavioral Research, 2010
In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…
Descriptors: Multivariate Analysis, Data Analysis, Data Interpretation, Computer Software
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Dozier, V. Casey; Sampson, James P.; Reardon, Robert C. – Professional Counselor, 2013
John Holland's Self-Directed Search (SDS) is a career assessment that consists of several booklets designed to be self-scored and self-administered. It simulates what a practitioner and an individual might do together in a career counseling session (e.g., review preferred activities and occupations; review competencies, abilities and possible…
Descriptors: Career Counseling, Simulation, Self Evaluation (Individuals), Delivery Systems
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Page, Stewart; Cramer, Kenneth M.; Page, Laura – Interchange: A Quarterly Review of Education, 2010
We present a data-based perspective concerning recent (e.g., 2008) "Maclean's" magazine rankings of Canadian universities, including cluster analysis of the 2008 data. Canadian universities empirically resemble and relate to each other in a manner different from their formal classification and final rank ordering in the…
Descriptors: Higher Education, Universities, Multivariate Analysis, Foreign Countries
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
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Ozturk, Halit; Kaufmann, Katrin – European Educational Research Journal, 2009
Europe as an "immigration continent" is going to become an "integration continent". Within this context continuing education has acquired an increasing meaning. Based on the German Socio-Economic Panel (SOEP) study data from 2001-04 the authors examine a broad spectrum of possible factors which may influence participation in…
Descriptors: Human Capital, Continuing Education, Foreign Countries, Migration
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