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Tellinghuisen, Joel – Journal of Chemical Education, 2015
The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…
Descriptors: Least Squares Statistics, Error of Measurement, Error Patterns, Chemistry
Xi, Nuo; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2014
A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Data, Computation
Chen, Fang; Chalhoub-Deville, Micheline – Language Testing, 2014
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Descriptors: Regression (Statistics), Language Tests, Language Proficiency, Mathematics Achievement
Pae, Hye K.; Greenberg, Daphne; Morris, Robin D. – Language Assessment Quarterly, 2012
The aim of this study was to apply the Rasch model to an analysis of the psychometric properties of the Peabody Picture Vocabulary Test--III Form A (PPVT--IIIA) items with struggling adult readers. The PPVT--IIIA was administered to 229 African American adults whose isolated word reading skills were between third and fifth grades. Conformity of…
Descriptors: African Americans, Test Items, Construct Validity, Test Validity
Bai, Yun; Poon, Wai-Yin – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, such as when individuals are randomly drawn from groups that are randomly drawn from a target population. Although 2-level data analysis in the context of structural equation modeling…
Descriptors: Structural Equation Models, Data Analysis, Simulation, Goodness of Fit
Savalei, Victoria; Kolenikov, Stanislav – Psychological Methods, 2008
Recently, R. D. Stoel, F. G. Garre, C. Dolan, and G. van den Wittenboer (2006) reviewed approaches for obtaining reference mixture distributions for difference tests when a parameter is on the boundary. The authors of the present study argue that this methodology is incomplete without a discussion of when the mixtures are needed and show that they…
Descriptors: Structural Equation Models, Goodness of Fit, Evaluation Methods, Statistical Analysis
Baghi, Heibatollah – 1990
The Maryland Functional Testing Program (MFTP) uses the Rasch model as the statistical framework for the analysis of test items and scores. This paper is designed to assist the reader in developing an understanding of the fit statistics in the Rasch model. Background materials on application of the Rasch model in statistical analysis of the MFTP…
Descriptors: Computer Assisted Testing, Computer Software, Equated Scores, Error of Measurement
Phillips, Gary W. – 1983
Ways in which the Statistical Package for the Social Sciences (SPSS) can be used to perform some Rasch analyses are described in detail. It is shown how SPSS and a set of item calibrations can be used to estimate person abilities, standard errors of measurement, test characteristic curve, test information curve, classification consistency on a…
Descriptors: Classification, Computer Software, Error of Measurement, Estimation (Mathematics)

Wolfle, Lee M.; Ethington, Corinna A. – Educational and Psychological Measurement, 1986
Using data from High School and Beyond, this study empirically investigated the extent of within-variable, between-occasion error covariances among variables included in educational achievement models. Little evidence was found to support the statement that reliability estimates for social background variables are inflated because of correlated…
Descriptors: Academic Achievement, Computer Software, Correlation, Equations (Mathematics)
Marsh, Herbert W.; Hocevar, Dennis – 1986
The advantages of applying confirmatory factor analysis (CFA) to multitrait-multimethod (MTMM) data are widely recognized. However, because CFA as traditionally applied to MTMM data incorporates single indicators of each scale (i.e., each trait/method combination), important weaknesses are the failure to: (1) correct appropriately for measurement…
Descriptors: Computer Software, Construct Validity, Correlation, Error of Measurement
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1985
The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Testing, Computer Software
Davis, Wesley D. – 1985
This study evaluated Krell's 1981-82 Scholastic Aptitude Test (SAT) preparatory series software purported to raise students' scores substantially after only a short term of computer-assisted instruction (CAI). Forty-eight college-bound juniors from Escambia County (Florida) were assigned to experimental and control groups. A two-phased pre- and…
Descriptors: Cognitive Style, College Bound Students, College Entrance Examinations, Computer Assisted Instruction