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Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming – Educational and Psychological Measurement, 2015
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…
Descriptors: Structural Equation Models, Statistical Analysis, Monte Carlo Methods, Computation
Adelman, James S.; Estes, Zachary – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Adelman, Marquis, Sabatos-DeVito, and Estes (2013) collected word naming latencies from 4 participants who read 2,820 words 50 times each. Their recommendation and practice was that R2 targets set for models should take into account subject idiosyncrasies as replicable patterns, equivalent to a subjects-as-fixed-effects assumption. In light of an…
Descriptors: Word Recognition, Naming, Individual Differences, Multiple Regression Analysis
de Leeuw, Christiaan; Klugkist, Irene – Multivariate Behavioral Research, 2012
In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…
Descriptors: Data, Multiple Regression Analysis, Bayesian Statistics, Models
Liu, Min; Lin, Tsung-I – Educational and Psychological Measurement, 2014
A challenge associated with traditional mixture regression models (MRMs), which rest on the assumption of normally distributed errors, is determining the number of unobserved groups. Specifically, even slight deviations from normality can lead to the detection of spurious classes. The current work aims to (a) examine how sensitive the commonly…
Descriptors: Regression (Statistics), Evaluation Methods, Indexes, Models
Morse, Brendan J.; Johanson, George A.; Griffeth, Rodger W. – Applied Psychological Measurement, 2012
Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…
Descriptors: Item Response Theory, Multiple Regression Analysis, Error of Measurement, Models
Williams, Ryan T. – ProQuest LLC, 2012
Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…
Descriptors: Multiple Regression Analysis, Meta Analysis, Evaluation Methods, Computation
McBee, Matthew – Gifted Child Quarterly, 2010
In gifted education research, it is common for outcome variables to exhibit strong floor or ceiling effects due to insufficient range of measurement of many instruments when used with gifted populations. Common statistical methods (e.g., analysis of variance, linear regression) produce biased estimates when such effects are present. In practice,…
Descriptors: Structural Elements (Construction), Gifted, Simulation, Regression (Statistics)
Woods, Carol M. – Multivariate Behavioral Research, 2008
Person fit is the degree to which an item response model fits for individual examinees. Reise (2000) described how two-level logistic regression can be used to detect heterogeneity in person fit, evaluate potential predictors of person fit heterogeneity, and identify potentially aberrant individuals. The method has apparently never been applied to…
Descriptors: Simulation, Test Reliability, Measures (Individuals), Item Response Theory
Shieh, Gwowen – Psychometrika, 2007
The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…
Descriptors: Sample Size, Monte Carlo Methods, Multiple Regression Analysis, Statistical Analysis

Aigner, Dennis J. – Management Science, 1972
Establishes an argument that questions the validity of one test'' of goodness-of-fit (the extent to which a series of obtained measures agrees with a series of theoretical measures) for the simulated time path of a simple endogenous (internally developed) variable in a simultaneous, perhaps dynamic econometric model. (Author)
Descriptors: Computer Science, Decision Making, Goodness of Fit, Models
Dusseldorp, Elise; Meulman, Jacqueline J. – Psychometrika, 2004
The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable with "multiple" covariates. The performance of RTA is compared to the classical…
Descriptors: Simulation, Psychometrics, Multiple Regression Analysis, Models
Grauer, Robert T.; Deutsch, Stuart J. – Educational Technology Systems, 1973
A simulation model of a suburban school district is synthesized by incorporating the results of multiple regression analysis within an Industrial Dynamics framework. The intermediate empirical analysis is described and results of the validation procedure for the final simulation model presented. Three computer experiments with the system model are…
Descriptors: Educational Development, Educational Research, Instructional Systems, Models
Kieras, David E. – 1979
Reading times can be a valuable source of data on comprehension processes, especially in the case of recording reading times on individual sentences in a passage. To overcome the methodological problems encountered in other research efforts concerning reading times, a multiple regression method was used to compare an ordinary language processing…
Descriptors: Cognitive Processes, Higher Education, Language Processing, Models
Greene, John F. – 1971
The major purpose of this study is to further the development of procedures which minimize current limitations of creativity instruments, thus yielding a reliable and functional means for assessing creativity. Computerized content analysis and multiple regression are employed to simulate the creativity ratings of trained judges. The computerized…
Descriptors: Behavioral Science Research, Computer Programs, Correlation, Creativity