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Thompson, Bruce – 1996
Multivariate normality is required for some statistical tests. This paper explores the implications of violating the assumption of multivariate normality and illustrates a graphical procedure for evaluating multivariate normality. The logic for using the multivariate bootstrap is presented. The multivariate bootstrap can be used when distribution…
Descriptors: Computer Assisted Testing, Computer Software, Correlation, Statistical Distributions
Chang, Shun-Wen; Twu, Bor-Yaun – 2001
To satisfy the security requirements of computerized adaptive tests (CATs), efforts have been made to control the exposure rates of optimal items directly by incorporating statistical methods into the item selection procedure. Since differences are likely to occur between the exposure control parameter derivation stage and the operational CAT…
Descriptors: Adaptive Testing, Computer Assisted Testing, Selection, Simulation

Wang, Jing-Jen – 1992
Approaches for norming skewed test score distributions are reviewed, and an analytical approach is proposed for norming the Behavior Assessment System for Children (BASC). Methods used in constructing norms for several well-known personality instruments that are reviewed include: (1) linear T-scores transformation in the Minnesota Multiphasic…
Descriptors: Computer Assisted Testing, Computer Oriented Programs, Inferences, Personality Measures
Jiang, Hai – 1999
The purpose of this paper is to describe the techniques used in establishing the concordance tables between the Test of English as a Foreign Language (TOEFL), paper and pencil (P&P), and computer-based testing (CBT) sections and total reported score scales. Listening, reading, and composite structure and essay scores plus a total score are…
Descriptors: Computer Assisted Testing, English (Second Language), Estimation (Mathematics), Scaling

van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob – Applied Psychological Measurement, 1999
Theoretical null distributions of several fit statistic have been derived for paper-and-pencil tests. Examined whether these distributions also hold for computerized adaptive tests through simulation. Rates for two statistics studied were found to be similar in most cases. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Goodness of Fit, Item Response Theory

Nering, Michael L. – Applied Psychological Measurement, 1997
Evaluated the distribution of person fit within the computerized-adaptive testing (CAT) environment through simulation. Found that, within the CAT environment, these indexes tend not to follow a standard normal distribution. Person fit indexes had means and standard deviations that were quite different from the expected. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Error of Measurement, Item Response Theory

Dodd, Barbara G.; Koch, William R. – Educational and Psychological Measurement, 1994
Simulated data were used to investigate the impact of characteristics of threshold values (number, symmetry, and distance between adjacent threshold values) and delta values on the distribution of item information in the successive intervals Rasch model. Implications for computerized adaptive attitude measurement are discussed. (SLD)
Descriptors: Adaptive Testing, Attitude Measures, Computer Assisted Testing, Item Response Theory
Nandakumar, Ratna; Roussos, Louis – 1997
This paper investigates the performance of CATSIB (a modified version of the SIBTEST computer program) to assess differential item functioning (DIF) in the context of computerized adaptive testing (CAT). One of the distinguishing features of CATSIB is its theoretically built-in regression correction to control for the Type I error rates when the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Bias, Power (Statistics)
Zwick, Rebecca – 1995
This paper describes a study, now in progress, of new methods for representing the sampling variability of Mantel-Haenszel differential item functioning (DIF) results, based on the system for categorizing the severity of DIF that is now in place at the Educational Testing Service. The methods, which involve a Bayesian elaboration of procedures…
Descriptors: Adaptive Testing, Bayesian Statistics, Classification, Computer Assisted Testing

Luecht, Richard M.; Hirsch, Thomas M. – Applied Psychological Measurement, 1992
Derivations of several item selection algorithms for use in fitting test items to target information functions (IFs) are described. These algorithms, which use an average growth approximation of target IFs, were tested by generating six test forms and were found to provide reliable fit. (SLD)
Descriptors: Algorithms, Computer Assisted Testing, Equations (Mathematics), Goodness of Fit

Wainer, Howard; And Others – Journal of Educational Measurement, 1992
Computer simulations were run to measure the relationship between testlet validity and factors of item pool size and testlet length for both adaptive and linearly constructed testlets. Making a testlet adaptive yields only modest increases in aggregate validity because of the peakedness of the typical proficiency distribution. (Author/SLD)
Descriptors: Adaptive Testing, Comparative Testing, Computer Assisted Testing, Computer Simulation

Dodd, Barbara G.; And Others – Educational and Psychological Measurement, 1993
Effects of the following variables on performance of computerized adaptive testing (CAT) procedures for the partial credit model (PCM) were studied: (1) stopping rule for terminating CAT; (2) item pool size; and (3) distribution of item difficulties. Implications of findings for CAT systems based on the PCM are discussed. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Simulation, Difficulty Level
Ito, Kyoko; Sykes, Robert C. – 1994
Responses to previously calibrated items administered in a computerized adaptive testing (CAT) mode may be used to recalibrate the items. This live-data simulation study investigated the possibility, and limitations, of on-line adaptive recalibration of precalibrated items. Responses to items of a Rasch-based paper-and-pencil licensure examination…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level