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Skrondal, Anders; Kuha, Jouni – Psychometrika, 2012
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Descriptors: Computation, Maximum Likelihood Statistics, Error of Measurement, Regression (Statistics)
Davis-Stober, Clintin P. – Psychometrika, 2011
Many researchers have demonstrated that fixed, exogenously chosen weights can be useful alternatives to Ordinary Least Squares (OLS) estimation within the linear model (e.g., Dawes, Am. Psychol. 34:571-582, 1979; Einhorn & Hogarth, Org. Behav. Human Perform. 13:171-192, 1975; Wainer, Psychol. Bull. 83:213-217, 1976). Generalizing the approach of…
Descriptors: Least Squares Statistics, Error of Measurement, Geometry, Computation
Molenaar, Dylan; Dolan, Conor V.; de Boeck, Paul – Psychometrika, 2012
The Graded Response Model (GRM; Samejima, "Estimation of ability using a response pattern of graded scores," Psychometric Monograph No. 17, Richmond, VA: The Psychometric Society, 1969) can be derived by assuming a linear regression of a continuous variable, Z, on the trait, [theta], to underlie the ordinal item scores (Takane & de Leeuw in…
Descriptors: Simulation, Regression (Statistics), Psychometrics, Item Response Theory
Battauz, Michela; Bellio, Ruggero – Psychometrika, 2011
This paper proposes a structural analysis for generalized linear models when some explanatory variables are measured with error and the measurement error variance is a function of the true variables. The focus is on latent variables investigated on the basis of questionnaires and estimated using item response theory models. Latent variable…
Descriptors: Error of Measurement, Structural Equation Models, Computation, Item Response Theory
Culpepper, Steven Andrew – Psychometrika, 2012
The study of prediction bias is important and the last five decades include research studies that examined whether test scores differentially predict academic or employment performance. Previous studies used ordinary least squares (OLS) to assess whether groups differ in intercepts and slopes. This study shows that OLS yields inaccurate inferences…
Descriptors: Academic Achievement, Prediction, Measurement, Least Squares Statistics
Sijtsma, Klaas – Psychometrika, 2009
This discussion paper argues that both the use of Cronbach's alpha as a reliability estimate and as a measure of internal consistency suffer from major problems. First, alpha always has a value, which cannot be equal to the test score's reliability given the inter-item covariance matrix and the usual assumptions about measurement error. Second, in…
Descriptors: Measurement, Error of Measurement, Scores, Computation
Chang, Yuan-chin Ivan; Lu, Hung-Yi – Psychometrika, 2010
Item calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration…
Descriptors: Test Items, Educational Testing, Adaptive Testing, Measurement
del Pino, Guido; San Martin, Ernesto; Gonzalez, Jorge; De Boeck, Paul – Psychometrika, 2008
This paper analyzes the sum score based (SSB) formulation of the Rasch model, where items and sum scores of persons are considered as factors in a logit model. After reviewing the evolution leading to the equality between their maximum likelihood estimates, the SSB model is then discussed from the point of view of pseudo-likelihood and of…
Descriptors: Computation, Models, Scores, Evaluation Methods
Battauz, Michela; Bellio, Ruggero; Gori, Enrico – Psychometrika, 2008
The achievement level is a variable measured with error, that can be estimated by means of the Rasch model. Teacher grades also measure the achievement level but they are expressed on a different scale. This paper proposes a method for combining these two scores to obtain a synthetic measure of the achievement level based on the theory developed…
Descriptors: Academic Achievement, Measurement, Error of Measurement, Computation
Kim, Jee-Seon; Frees, Edward W. – Psychometrika, 2007
When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…
Descriptors: Simulation, Measurement, Error of Measurement, Computation
Bollen, Kenneth A.; Maydeu-Olivares, Albert – Psychometrika, 2007
This paper presents a new polychoric instrumental variable (PIV) estimator to use in structural equation models (SEMs) with categorical observed variables. The PIV estimator is a generalization of Bollen's (Psychometrika 61:109-121, 1996) 2SLS/IV estimator for continuous variables to categorical endogenous variables. We derive the PIV estimator…
Descriptors: Structural Equation Models, Simulation, Robustness (Statistics), Computation
Haberman, Shelby J. – Psychometrika, 2006
When a simple random sample of size n is employed to establish a classification rule for prediction of a polytomous variable by an independent variable, the best achievable rate of misclassification is higher than the corresponding best achievable rate if the conditional probability distribution is known for the predicted variable given the…
Descriptors: Bias, Computation, Sample Size, Classification