@booklet {1604,
	title = {Item and passage selection algorithm simulations for a computerized adaptive version of the verbal section of the Medical College Admission Test (MCAT)},
	year = {2001},
	address = {MCAT Monograph Series},
	author = {Smith, R. W. and Plake, B. S. and De Ayala, R. J.,}
}
@article {104,
	title = {Computerized adaptive testing with polytomous items},
	journal = {Applied Psychological Measurement},
	volume = {19},
	year = {1995},
	pages = {5{\textendash}22.},
	abstract = {Discusses polytomous item response theory models and the research that has been conducted to investigate a variety of possible operational procedures (item bank, item selection, trait estimation, stopping rule) for polytomous model-based computerized adaptive testing (PCAT). Studies are reviewed that compared PCAT systems based on competing item response theory models that are appropriate for the same measurement objective, as well as applications of PCAT in marketing and educational psychology. Directions for future research using PCAT are suggested.},
	author = {Dodd, B. G. and De Ayala, R. J., and Koch, W. R.}
}
@article {106,
	title = {Computerized adaptive testing using the partial credit model: Effects of item pool characteristics and different stopping rules},
	journal = {Educational and Psychological Measurement},
	volume = {53},
	number = {1},
	year = {1993},
	pages = {61-77.},
	abstract = {Simulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the variety of CAT conditions than the minimum information stopping rule. In addition it was found that item pools that consisted of as few as 30 items were adequate for CAT provided that the item pool was of medium difficulty. The implications of these findings for implementing CAT systems based on the partial credit model are discussed. },
	author = {Dodd, B. G. and Koch, W. R. and De Ayala, R. J.,}
}
@article {526,
	title = {The influence of dimensionality on CAT ability estimation},
	journal = {Educational and Psychological Measurement},
	volume = {52},
	year = {1992},
	pages = {513-528},
	author = {De Ayala, R. J.,}
}
@article {525,
	title = {The nominal response model in computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {16},
	year = {1992},
	pages = {327-343},
	author = {De Ayala, R. J.,}
}
@article {98,
	title = {A simulation and comparison of flexilevel and Bayesian computerized adaptive testing},
	journal = {Journal of Educational Measurement},
	volume = {27},
	number = {3},
	year = {1990},
	pages = {227-239},
	abstract = {Computerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee{\textquoteright}s ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord{\textquoteright}s flexilevel testing procedure (flexilevel CAT) with an item response theory-based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36- and 18-item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory-based CAT.},
	keywords = {computerized adaptive testing},
	author = {De Ayala, R. J., and Dodd, B. G. and Koch, W. R.}
}
@article {524,
	title = {A comparison of the nominal response model and the three-parameter logistic model in computerized adaptive testing},
	journal = {Educational and Psychological Measurement},
	volume = {49},
	year = {1989},
	pages = {789-805},
	author = {De Ayala, R. J.,}
}
@article {532,
	title = {Operational characteristics of adaptive testing procedures using the graded response model},
	journal = {Applied Psychological Measurement},
	volume = {13},
	year = {1989},
	pages = {129-143},
	author = {Dodd, B. G. and Koch, W. R. and De Ayala, R. J.,}
}
@conference {909,
	title = {Computerized adaptive attitude measurement: A comparison of the graded response and rating scale models},
	booktitle = {Paper presented at the annual meeting of the American Educational Research Association},
	year = {1988},
	address = {New Orleans},
	author = {Dodd, B. G. and Koch, W. R. and De Ayala, R. J.,}
}
@article {97,
	title = {Computerized adaptive testing: A comparison of the nominal response model and the three parameter model},
	journal = {Dissertation Abstracts International},
	volume = {48},
	number = {10-B},
	year = {1988},
	pages = {3148},
	keywords = {computerized adaptive testing},
	author = {De Ayala, R. J.,}
}
@conference {899,
	title = {Computerized adaptive testing: A comparison of the nominal response model and the three-parameter logistic model},
	booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education},
	year = {1987},
	address = {Washington DC},
	author = {De Ayala, R. J., and Koch, W. R.}
}
@article {528,
	title = {ALPHATAB: A lookup table for Bayesian computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {9},
	year = {1985},
	pages = {326},
	author = {De Ayala, R. J., and Koch, W. R.}
}
