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Doebler, Anna; Doebler, Philipp; Holling, Heinz – Psychometrika, 2013
The common way to calculate confidence intervals for item response theory models is to assume that the standardized maximum likelihood estimator for the person parameter [theta] is normally distributed. However, this approximation is often inadequate for short and medium test lengths. As a result, the coverage probabilities fall below the given…
Descriptors: Foreign Countries, Item Response Theory, Computation, Hypothesis Testing
Downey, W. Scott; Schetzsle, Stacey – Marketing Education Review, 2012
Asynchronous assessment, which includes quizzes or exams online or outside class, offers marketing educators an opportunity to make more efficient use of class time and to enhance students' learning experiences by giving them more flexibility and choice in their assessment environment. In this paper, we examine the performance difference between…
Descriptors: Marketing, Lecture Method, Asynchronous Communication, Synchronous Communication
Wells, Craig S.; Cohen, Allan S.; Patton, Jeffrey – International Journal of Testing, 2009
A primary concern with testing differential item functioning (DIF) using a traditional point-null hypothesis is that a statistically significant result does not imply that the magnitude of DIF is of practical interest. Similarly, for a given sample size, a non-significant result does not allow the researcher to conclude the item is free of DIF. To…
Descriptors: Test Bias, Test Items, Statistical Analysis, Hypothesis Testing
Monahan, Patrick O.; Stump, Timothy E.; Finch, Holmes; Hambleton, Ronald K. – Applied Psychological Measurement, 2007
DETECT is a nonparametric "full" dimensionality assessment procedure that clusters dichotomously scored items into dimensions and provides a DETECT index of magnitude of multidimensionality. Four factors (test length, sample size, item response theory [IRT] model, and DETECT index) were manipulated in a Monte Carlo study of bias, standard error,…
Descriptors: Test Length, Sample Size, Monte Carlo Methods, Geometric Concepts
Maxwell, Scott E. – 1979
Arguments have recently been put forth that standard textbook procedures for determining the sample size necessary to achieve a certain level of power in a completely randomized design are incorrect when the dependent variable is fallible because they ignore measurement error. In fact, however, there are several correct procedures, one of which is…
Descriptors: Hypothesis Testing, Mathematical Formulas, Power (Statistics), Predictor Variables
Epstein, Kenneth I.; Steinheiser, Frederick H., Jr. – 1978
A multiparameter, programmable model was developed to examine the interactive influence of certain parameters on the probability of deciding that an examinee had attained a specified degree of mastery. It was applied within the simulated context of performance testing of military trainees. These parameters included: (1) the number of assumed…
Descriptors: Academic Ability, Bayesian Statistics, Cutting Scores, Hypothesis Testing
Frick, Theodore W. – 1986
The sequential probability ratio test (SPRT), developed by Abraham Wald, is one statistical model available for making mastery decisions during computer-based criterion referenced tests. The predictive validity of the SPRT was empirically investigated with two different and relatively large item pools with heterogeneous item parameters. Graduate…
Descriptors: Achievement Tests, Adaptive Testing, Classification, Comparative Analysis

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