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Direct linkBen Kelcey; Fangxing Bai; Amota Ataneka; Yanli Xie; Kyle Cox – Society for Research on Educational Effectiveness, 2024
We develop a structural after measurement (SAM) method for structural equation models (SEMs) that accommodates missing data. The results show that the proposed SAM missing data estimator outperforms conventional full information (FI) estimators in terms of convergence, bias, and root-mean-square-error in small-to-moderate samples or large samples…
Descriptors: Structural Equation Models, Research Problems, Error of Measurement, Maximum Likelihood Statistics
Peer reviewedKeith, Timothy Z. – Remedial and Special Education (RASE), 1993
This overview of nonexperimental causal research methods focuses on latent variable structural equation modeling using the LISREL computer program. An extended example in special education is used to present LISREL as an extension of structural equations analysis (path analysis) and as a method of reducing the effects of error in research.…
Descriptors: Causal Models, Computer Oriented Programs, Computer Software, Data Analysis
Peer reviewedEwert, Alan; Sibthorp, Jim – Journal of Experiential Education, 2000
Multivariate analytic techniques offer useful research methods that permit the experiential educator to test theoretical models, analyze the effects of several variables acting together, and predict the effects of one set of variables upon another set of variables. Several of these techniques are discussed, including analysis of variance, multiple…
Descriptors: Adventure Education, Analysis of Covariance, Analysis of Variance, Educational Research
