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Fan, Xitao; Sivo, Stephen A. – Multivariate Behavioral Research, 2007
The search for cut-off criteria of fit indices for model fit evaluation (e.g., Hu & Bentler, 1999) assumes that these fit indices are sensitive to model misspecification, but not to different types of models. If fit indices were sensitive to different types of models that are misspecified to the same degree, it would be very difficult to establish…
Descriptors: Structural Equation Models, Criteria, Monte Carlo Methods, Factor Analysis
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Viechtbauer, Wolfgang – Journal of Educational and Behavioral Statistics, 2007
Standardized effect sizes and confidence intervals thereof are extremely useful devices for comparing results across different studies using scales with incommensurable units. However, exact confidence intervals for standardized effect sizes can usually be obtained only via iterative estimation procedures. The present article summarizes several…
Descriptors: Intervals, Effect Size, Comparative Analysis, Monte Carlo Methods
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Zimmerman, Donald W. – Educational and Psychological Measurement, 2007
Properties of the Spearman correction for attenuation were investigated using Monte Carlo methods, under conditions where correlations between error scores exist as a population parameter and also where correlated errors arise by chance in random sampling. Equations allowing for all possible dependence among true and error scores on two tests at…
Descriptors: Monte Carlo Methods, Correlation, Sampling, Data Analysis
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Hwang, Heungsun; Takane, Yoshio; DeSarbo, Wayne S. – Multivariate Behavioral Research, 2007
The growth curve model has been a useful tool for the analysis of repeated measures data. However, it is designed for an aggregate-sample analysis based on the assumption that the entire sample of respondents are from a single homogenous population. Thus, this method may not be suitable when heterogeneous subgroups exist in the population with…
Descriptors: Equations (Mathematics), Antisocial Behavior, Computation, Child Behavior
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Cheung, Mike W. L. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mediators are variables that explain the association between an independent variable and a dependent variable. Structural equation modeling (SEM) is widely used to test models with mediating effects. This article illustrates how to construct confidence intervals (CIs) of the mediating effects for a variety of models in SEM. Specifically, mediating…
Descriptors: Structural Equation Models, Probability, Intervals, Sample Size
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Lee, Sik-Yum; Song, Xin-Yuan; Lu, Bin – Multivariate Behavioral Research, 2007
This article proposes an intuitive approach for predictive discriminant analysis with mixed continuous, dichotomous, and ordered categorical variables that are defined via an underlying multivariate normal distribution with a threshold specification. The classification rule is based on the comparison of the observed data logarithm probability…
Descriptors: Factor Analysis, Discriminant Analysis, Probability, Monte Carlo Methods
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Campuzano, Larissa; Dynarski, Mark; Agodini, Roberto; Rall, Kristina – National Center for Education Evaluation and Regional Assistance, 2009
In the No Child Left Behind Act (NCLB), Congress called for the U.S. Department of Education (ED) to conduct a rigorous study of the conditions and practices under which educational technology is effective in increasing student academic achievement. A 2007 report presenting study findings for the 2004-2005 school year, indicated that, after one…
Descriptors: Teacher Characteristics, Federal Legislation, Academic Achievement, Computer Software
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Klein Entink, Rinke H.; Kuhn, Jorg-Tobias; Hornke, Lutz F.; Fox, Jean-Paul – Psychological Methods, 2009
In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…
Descriptors: Psychological Studies, Monte Carlo Methods, Markov Processes, Educational Assessment
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Hafdahl, Adam R. – Journal of Educational and Behavioral Statistics, 2007
The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…
Descriptors: Monte Carlo Methods, Correlation, Meta Analysis, Matrices
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Monahan, Patrick O.; Lee, Won-Chan; Ankenmann, Robert D. – Journal of Educational Measurement, 2007
A Monte Carlo simulation technique for generating dichotomous item scores is presented that implements (a) a psychometric model with different explicit assumptions than traditional parametric item response theory (IRT) models, and (b) item characteristic curves without restrictive assumptions concerning mathematical form. The four-parameter beta…
Descriptors: True Scores, Psychometrics, Monte Carlo Methods, Correlation
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Yao, Lihua; Boughton, Keith A. – Applied Psychological Measurement, 2007
Several approaches to reporting subscale scores can be found in the literature. This research explores a multidimensional compensatory dichotomous and polytomous item response theory modeling approach for subscale score proficiency estimation, leading toward a more diagnostic solution. It also develops and explores the recovery of a Markov chain…
Descriptors: Psychometrics, Markov Processes, Classification, Item Response Theory
Chason, Walter M.; And Others – 1996
R. C. Blair (1991) developed tables of critical values for the generalized "t" and generalized rank sum tests that do not suffer inflation of Type I error. This study evaluated the critical values generated by Blair for situations in which sample size varies more than a maximum of a factor of two. The accuracy of the values was explored…
Descriptors: Monte Carlo Methods, Sample Size, Scores, Simulation
Brown, R. L. – 1987
This paper explores the use of K. G. Joreskog's (1970) congeneric modeling approach to reliability using censored quantitative variables. Two Monte Carlo studies were conducted. The first explored the robustness of Normal Theory Generalized Least-Squares (NTGLS) estimates for a single-factor congeneric model across several sample sizes…
Descriptors: Interrater Reliability, Monte Carlo Methods, Sample Size
Borgen, Fred H.; Muchinsky, Paul M. – 1979
The purposes of this study are to compare alternative statistical techniques for analysis of the kinds of qualitative data commonly obtained in educational settings. Distinctions between chi-square based measures for contingency tables and proportional reduction of error measures of the strength of association are reviewed, and it is argued that…
Descriptors: Monte Carlo Methods, Sample Size, Statistical Analysis
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Mullen, Kenneth; Ennis, Daniel M. – Psychometrika, 1987
Multivariate models for the triangular and duo-trio methods are described, and theoretical methods are compared to a Monte Carlo simulation. Implications are discussed for a new theory of multidimensional scaling which challenges the traditional assumption that proximity measures and perceptual distances are monotonically related. (Author/GDC)
Descriptors: Mathematical Models, Monte Carlo Methods, Multidimensional Scaling
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