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Fan, Xitao; Nowell, Dana L. – Gifted Child Quarterly, 2011
This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…
Descriptors: Research Design, Educational Research, Statistical Analysis, Inferences
Shih, Tse-Hua; Fan, Xitao – Educational Research Review, 2009
This meta-analysis examined 35 study results within last 10 years that directly compared the response rates of e-mail versus mail surveys. Individual studies reported inconsistent findings concerning the response rate difference between e-mail and mail surveys, but e-mail surveys generally have lower response rate (about 20% lower on the average)…
Descriptors: Mail Surveys, Response Rates (Questionnaires), Comparative Analysis, Meta Analysis
Fan, Xitao; Sivo, Stephen A. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
In research concerning model invariance across populations, researchers have discussed the limitations of the conventional chi-square difference test ([Delta] chi-square test). There have been some research efforts in using goodness-of-fit indexes (i.e., [Delta]goodness-of-fit indexes) for assessing multisample model invariance, and some specific…
Descriptors: Monte Carlo Methods, Goodness of Fit, Statistical Analysis, Simulation
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

Fan, Xitao – Structural Equation Modeling, 1997
The relationship between structural equation modeling (SEM) and canonical correlation analysis (CCA) is illustrated. The representation of CCA in SEM may provide interpretive information not available from conventional CCA. Hierarchically, the relationship suggests that SEM is a more general analytic approach. (SLD)
Descriptors: Correlation, Research Methodology, Statistical Analysis, Structural Equation Models
Fan, Xitao; Fan, Xiaotao – Journal of Experimental Education, 2005
The authors investigated 2 issues concerning the power of latent growth modeling (LGM) in detecting linear growth: the effect of the number of repeated measurements on LGM's power in detecting linear growth and the comparison between LGM and some other approaches in terms of power for detecting linear growth. A Monte Carlo simulation design was…
Descriptors: Statistical Analysis, Sample Size, Monte Carlo Methods, Structural Equation Models
Hallahan, Daniel P.; Keller, Clayton E.; Martinez, Elizabeth A.; Byrd, E. Stephen; Gelman, Jennifer A.; Fan, Xitao – Exceptional Children, 2007
This study compared interstate variability of prevalence rates for special education categories from 1984 to 1985 through 2001 to 2002, using the coefficient of variation (CV), which is designed to compare variances when the means of the groups compared are radically different. The category of learning disabilities, presumed by many to be the most…
Descriptors: Learning Disabilities, Hearing Impairments, Language Impairments, Speech Impairments

Fan, Xitao – Educational and Psychological Measurement, 1998
This study empirically examined the behaviors of item and person statistics derived from item response theory and classical test theory, focusing on item and person statistics and using a large-scale statewide assessment. Findings show that the person and item statistics from the two measurement frameworks are quite comparable. (SLD)
Descriptors: Item Response Theory, State Programs, Statistical Analysis, Test Items
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