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Xu Qin; Lijuan Wang – Grantee Submission, 2023
Research questions regarding how, for whom, and where a treatment achieves its effect on an outcome have become increasingly valued in substantive research. Such questions can be answered by causal moderated mediation analysis, which assesses the heterogeneity of the mediation mechanism underlying the treatment effect across individual and…
Descriptors: Causal Models, Mediation Theory, Computer Software, Statistical Analysis
Pustejovsky, James E.; Swan, Daniel M.; English, Kyle W. – Grantee Submission, 2019
There has been growing interest in using statistical methods to analyze data and estimate effect size indices from studies that use single-case designs (SCDs), as a complement to traditional visual inspection methods. The validity of a statistical method rests on whether its assumptions are plausible representations of the process by which the…
Descriptors: Measurement Techniques, Statistical Analysis, Data, Outcome Measures
Levin, Joel R.; Ferron, John M.; Kratochwill, Thomas R. – Journal of School Psychology, 2012
In this four-investigation Monte Carlo simulation study, we examined the properties of nonparametric randomization and permutation statistical tests applied to single-case ABAB...AB and alternating treatment designs based on either systematically alternating or randomly determined phase assignments. Contrary to previous admonitions, when…
Descriptors: Intervention, Research Design, Nonparametric Statistics, School Psychology
Gilstrap, Donald L. – Complicity: An International Journal of Complexity and Education, 2013
In addition to qualitative methods presented in chaos and complexity theories in educational research, this article addresses quantitative methods that may show potential for future research studies. Although much in the social and behavioral sciences literature has focused on computer simulations, this article explores current chaos and…
Descriptors: Educational Research, Social Science Research, Behavioral Science Research, Statistical Analysis
Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K. – Multivariate Behavioral Research, 2012
Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…
Descriptors: Questionnaires, Data Analysis, Computation, Monte Carlo Methods
Maraun, Michael D.; Slaney, Kathleen – Multivariate Behavioral Research, 2005
MAXCOV-HITMAX was invented by Paul Meehl as a tool for the detection of latent taxonic structures (i.e., structures in which the latent variable, u, is not continuously, but rather Bernoulli, distributed). It involves the examination of the shape of a certain conditional covariance function and is based on Meehl's claims that (R1) Taxonic…
Descriptors: Multivariate Analysis, Hypothesis Testing, Monte Carlo Methods, Behavioral Science Research
Kelley, Ken – Educational and Psychological Measurement, 2005
The standardized group mean difference, Cohen's "d", is among the most commonly used and intuitively appealing effect sizes for group comparisons. However, reporting this point estimate alone does not reflect the extent to which sampling error may have led to an obtained value. A confidence interval expresses the uncertainty that exists between…
Descriptors: Intervals, Sampling, Integrity, Effect Size
Koffler, Stephen L. – 1976
The power of the classical Linear Discriminant Function (LDF) is compared, using Monte Carlo techniques with five other procedures for classifying observations from certain non-normal distributions. The alternative procedures considered are the Quadratic Discriminant Function, a Nearest Neighbor Procedure with Probability Blocks, and three density…
Descriptors: Behavioral Science Research, Classification, Comparative Analysis, Discriminant Analysis
Robey, Randall R.; Barcikowski, Robert S. – 1986
This paper reports the results of a Monte Carlo investigation of Type I errors in the single group repeated measures design where multiple measures are collected from each observational unit at each measurement occasion. The Type I error of three multivariate tests were examined. These were the doubly multivariate F test, the multivariate mixed…
Descriptors: Analysis of Variance, Behavioral Science Research, Comparative Analysis, Hypothesis Testing