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Leite, Walter L.; Aydin, Burak; Gurel, Sungur – Journal of Experimental Education, 2019
This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove…
Descriptors: Probability, Weighted Scores, Monte Carlo Methods, Statistical Bias
McCaffrey, Daniel F.; Lockwood, J. R.; Setodji, Claude M. – Society for Research on Educational Effectiveness, 2011
Inverse probability weighting (IPW) estimates are widely used in applications where data are missing due to nonresponse or censoring or in observational studies of causal effects where the counterfactuals cannot be observed. This extensive literature has shown the estimators to be consistent and asymptotically normal under very general conditions,…
Descriptors: Computation, Probability, Weighted Scores, Error of Measurement
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Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
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Qian, Jiahe – ETS Research Report Series, 2006
Weighting and variance estimation are two statistical issues involved in survey data analysis for large-scale assessment programs such as the Higher Education Information and Communication Technology (ICT) Literacy Assessment. Because survey data are always acquired by probability sampling, to draw unbiased or almost unbiased inferences for the…
Descriptors: Weighted Scores, Sampling, Statistical Analysis, Higher Education