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Finch, W. Holmes; Finch, Maria E. Hernandez – Practical Assessment, Research & Evaluation, 2016
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
Descriptors: Sample Size, Statistical Analysis, Regression (Statistics), Predictor Variables
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Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad – Journal of Experimental Education, 2017
Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…
Descriptors: Predictor Variables, Models, Predictive Measurement, Statistical Analysis
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Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
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Altmeyer, Michael; Schweizer, Karl; Reiss, Siegbert; Ren, Xuezhu; Schreiner, Michael – Learning and Individual Differences, 2013
Performance in working memory and short-term memory tasks was employed for predicting performance in a long-term memory task in order to find out about the underlying processes. The types of memory were represented by versions of the Posner Task, the Backward Counting Task and the Sternberg Task serving as measures of long-term memory, working…
Descriptors: Short Term Memory, Long Term Memory, Memory, Performance
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Hoyt, Jeff E.; Howell, Scott L. – Journal of Continuing Higher Education, 2011
This article provides questionnaire items and a theoretical model of factors predictive of customer loyalty for use by administrators to determine ways to increase repeat purchasing in their continuing education programs. Prior studies in the literature are discussed followed by results of applying the model at one institution and a discussion of…
Descriptors: Continuing Education, Marketing, Satisfaction, Evaluation
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Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
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Adedokun, Omolola A.; Childress, Amy L.; Burgess, Wilella D. – American Journal of Evaluation, 2011
A theory-driven approach to evaluation (TDE) emphasizes the development and empirical testing of conceptual models to understand the processes and mechanisms through which programs achieve their intended goals. However, most reported applications of TDE are limited to large-scale experimental/quasi-experimental program evaluation designs. Very few…
Descriptors: Feedback (Response), Program Evaluation, Structural Equation Models, Testing
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Knofczynski, Gregory T.; Mundfrom, Daniel – Educational and Psychological Measurement, 2008
When using multiple regression for prediction purposes, the issue of minimum required sample size often needs to be addressed. Using a Monte Carlo simulation, models with varying numbers of independent variables were examined and minimum sample sizes were determined for multiple scenarios at each number of independent variables. The scenarios…
Descriptors: Sample Size, Monte Carlo Methods, Predictor Variables, Prediction
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Cress, Ulrike – International Journal of Computer-Supported Collaborative Learning, 2008
Per definition, CSCL research deals with the data of individuals nested in groups, and the influence of a specific learning setting on the collaborative process of learning. Most well-established statistical methods are not able to analyze such nested data adequately. This article describes the problems which arise when standard methods are…
Descriptors: Predictor Variables, Statistical Analysis, Research Needs, Educational Research
Donoghue, John R.; Jenkins, Frank – 1992
Monte Carlo methods were used to investigate the effect of misspecification of the second level in a two-level hierarchical linear model (HLM). Sample composition, heterogeneity of the group size, level of intraclass correlation, and correlation between second-level predictors were manipulated. Each of 20 generated data sets was analyzed nine…
Descriptors: Correlation, Estimation (Mathematics), Models, Monte Carlo Methods
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Finch, W. Holmes; Schneider, Mercedes K. – Educational and Psychological Measurement, 2006
This study compares the classification accuracy of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR), and classification and regression trees (CART) under a variety of data conditions. Past research has generally found comparable performance of LDA and LR, with relatively less research on QDA and…
Descriptors: Classification, Sample Size, Effect Size, Discriminant Analysis
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Howell-White, Sandra; Gaboda, Dorothy; Rosato, Nancy Scotto; Lucas, Judith A. – Gerontologist, 2006
Purpose: This research provides state policy makers and others interested in developing needs-based reimbursement models for Medicaid-funded assisted living with an evaluation of different methodologies that affect the structure and outcomes of these models. Design and Methods: We used assessment data from Medicaid-enrolled assisted living…
Descriptors: Models, Statistical Analysis, Individual Characteristics, Health Services