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Delucchi, Kevin L. – 1981
The proper use of Pearson's chi-square for the analysis of contingency tables is reviewed. A 1949 article by Lewis and Burke, in which they cite nine primary sources of error in the use of chi-square, serves as the basis of the review. Those nine sources of error are re-examined in light of current research. In addition, techniques and research on…
Descriptors: Educational Research, Error of Measurement, Goodness of Fit, Literature Reviews
de Gruijter, Dato N. M. – 1980
In a situation where the population distribution of latent trait scores can be estimated, the ordinary maximum likelihood estimator of latent trait scores may be improved upon by taking the estimated population distribution into account. In this paper empirical Bayes estimators are compared with the liklihood estimator for three samples of 300…
Descriptors: Bayesian Statistics, Comparative Analysis, Goodness of Fit, Item Sampling
Samejima, Fumiko – 1980
Many combinations of a method and an approach for estimating the operating characteristics of the graded item responses, without assuming any mathematical forms, have been produced. In these methods, a set of items whose characteristics are known, or Old Test, is used, which has a large, constant amount of test information throughout the interval…
Descriptors: Difficulty Level, Item Analysis, Latent Trait Theory, Least Squares Statistics
Samejima, Fumiko – 1980
The effect of prior information in Bayesian estimation is considered, mainly from the standpoint of objective testing. In the estimation of a parameter belonging to an individual, the prior information is, in most cases, the density function of the population to which the individual belongs. Bayesian estimation was compared with maximum likelihood…
Descriptors: Bayesian Statistics, Computer Assisted Testing, Information Utilization, Latent Trait Theory
Kolen, Michael J.; Whitney, Douglas R. – 1978
The application of latent trait theory to classroom tests necessitates the use of small sample sizes for parameter estimation. Computer generated data were used to assess the accuracy of estimation of the slope and location parameters in the two parameter logistic model with fixed abilities and varying small sample sizes. The maximum likelihood…
Descriptors: Difficulty Level, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewedEthington, Corinna A. – Journal of Experimental Education, 1987
This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…
Descriptors: Computer Software, Estimation (Mathematics), Factor Analysis, Least Squares Statistics
Peer reviewedSwaminathan, Hariharan; Gifford, Janice A. – Psychometrika, 1986
A joint Bayesian estimation procedure for estimating parameters in the three-parameter logistic model is developed. Simulation studies show that the Bayesian procedure (1) ensures that the estimates stay in the parameter space and (2) produces better estimates than the joint maximum likelihood procedure. (Author/BS)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Goodness of Fit, Latent Trait Theory
Leonard, Tom; Novick, Melvin R. – Journal of Education Statistics, 1986
A general approach is proposed for modeling the structure of a r x s contingency table and for drawing marginal inferences about all parameters (e.g., interaction effects) in the model. The main approach is relevant whenever rs minus r minus s plus 1 is greater than or equal to 5. Military aptitude test data is used as illustration. (Author/LMO)
Descriptors: Aptitude Tests, Bayesian Statistics, Goodness of Fit, Interaction
de Leeuw, Jan; Kreft, Ita – Journal of Education Statistics, 1986
A statistical model is proposed for both contextual analysis and slopes as outcomes analysis. A random coefficient model is investigated in detail. Various estimation models are reviewed and applied to a Dutch school-career example. (Author/LMO)
Descriptors: Elementary Education, Estimation (Mathematics), Least Squares Statistics, Mathematical Models
Ban, Jae-Chun; Hanson, Bradley A.; Wang, Tianyou; Yi, Qing; Harris, Deborah J. – 2000
The purpose of this study was to compare and evaluate five online pretest item calibration/scaling methods in computerized adaptive testing (CAT): (1) the marginal maximum likelihood estimate with one-EM cycle (OEM); (2) the marginal maximum likelihood estimate with multiple EM cycles (MEM); (3) Stocking's Method A (M. Stocking, 1988); (4)…
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Estimation (Mathematics)
Yi, Qing; Wang, Tianyou; Ban, Jae-Chun – 2000
Error indices (bias, standard error of estimation, and root mean square error) obtained on different scales of measurement under different test termination rules in a computerized adaptive test (CAT) context were examined. Four ability estimation methods were studied: (1) maximum likelihood estimation (MLE); (2) weighted likelihood estimation…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Error of Measurement
Peer reviewedRezmovic, Eva Lantos; Rezmovic, Victor – Educational and Psychological Measurement, 1981
A multitrait-multimethod matrix containing two methods of measuring 12 personality traits was analyzed and confirmatory factor analysis was applied to the data. Although unexplained variance remained, method factors and a general personality factor significantly improved the fit of a model containing only trait factors. (Author/RL)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Mathematical Models
Peer reviewedOlsson, Ulf – Multivariate Behavioral Research, 1979
The paper discusses the consequences for maximum likelihood factor analysis which may follow if the observed variables are ordinal with only a few scale steps. Results indicate that classification may lead to a substantial lack of fit of the model--an erroneous indication that more factors are needed. (Author/CTM)
Descriptors: Classification, Factor Analysis, Goodness of Fit, Maximum Likelihood Statistics
Peer reviewedAnderson, Ronald D. – Structural Equation Modeling, 1996
Goodness of fit indexes developed by R. P. McDonald (1989) and Satorra-Bentler scale correction methods (A. Satorra and P. M. Bentler, 1988) were studied. The Satorra-Bentler index is shown to have the least error under each distributional misspecification level when the model has correct structural specification. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Maximum Likelihood Statistics
Peer reviewedMcQuitty, Shaun – Structural Equation Modeling, 1997
LISREL 8 invokes a ridge option when maximum likelihood or generalized least squares are used to estimate a structural equation model with a nonpositive definite covariance or correlation matrix. Implications of the ridge option for model fit, parameter estimates, and standard errors are explored through two examples. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Least Squares Statistics


