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Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2016
Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…
Descriptors: Educational Experiments, Error of Measurement, Research Design, Statistical Analysis
McBee, Matthew T.; Peters, Scott J.; Waterman, Craig – Gifted Child Quarterly, 2014
Best practice in gifted and talented identification procedures involves making decisions on the basis of multiple measures. However, very little research has investigated the impact of different methods of combining multiple measures. This article examines the consequences of the conjunctive ("and"), disjunctive/complementary…
Descriptors: Best Practices, Ability Identification, Academically Gifted, Correlation
Longford, Nicholas T. – Journal of Educational and Behavioral Statistics, 2012
Statistical modeling of school effectiveness data was originally motivated by the dissatisfaction with the analysis of (school-leaving) examination results that took no account of the background of the students or regarded each school as an isolated unit of analysis. The application of multilevel analysis was generally regarded as a breakthrough,…
Descriptors: School Effectiveness, Data Analysis, Statistical Analysis, Statistical Studies
French, Brian F.; Finch, W. Holmes – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Confirmatory factor analytic (CFA) procedures can be used to provide evidence of measurement invariance. However, empirical evaluation has not focused on the accuracy of common CFA steps used to detect a lack of invariance across groups. This investigation examined procedures for detection of test structure differences across groups under several…
Descriptors: Factor Analysis, Structural Equation Models, Evaluation Criteria, Error of Measurement
Mapuranga, Raymond; Dorans, Neil J.; Middleton, Kyndra – ETS Research Report Series, 2008
In many practical settings, essentially the same differential item functioning (DIF) procedures have been in use since the late 1980s. Since then, examinee populations have become more heterogeneous, and tests have included more polytomously scored items. This paper summarizes and classifies new DIF methods and procedures that have appeared since…
Descriptors: Test Bias, Educational Development, Evaluation Methods, Statistical Analysis
Brandt, David A. – 1982
This report describes and evaluates the major computer software packages capable of computing standard errors for statistics estimated from complex samples. It first describes the problem and the proposed solutions. The two major programs presently available, SUPER CARP and OSIRIS, are described in general terms. The kinds of statistics available…
Descriptors: Analysis of Variance, Cluster Analysis, Computer Software Reviews, Correlation
Haladyna, Tom; Roid, Gale – 1976
Three approaches to the construction of achievement tests are compared: construct, operational, and empirical. The construct approach is based upon classical test theory and measures an abstract representation of the instructional objectives. The operational approach specifies instructional intent through instructional objectives, facet design,…
Descriptors: Academic Achievement, Achievement Tests, Career Development, Comparative Analysis