@article {17,
	title = {Rotating item banks versus restriction of maximum exposure rates in computerized adaptive testing},
	journal = {Spanish Journal of Psychology},
	volume = {11},
	number = {2},
	year = {2008},
	note = {Barrada, Juan RamonOlea, JulioAbad, Francisco JoseResearch Support, Non-U.S. Gov{\textquoteright}tSpainThe Spanish journal of psychologySpan J Psychol. 2008 Nov;11(2):618-25.},
	pages = {618-625},
	edition = {2008/11/08},
	abstract = {<p>If examinees were to know, beforehand, part of the content of a computerized adaptive test, their estimated trait levels would then have a marked positive bias. One of the strategies to avoid this consists of dividing a large item bank into several sub-banks and rotating the sub-bank employed (Ariel, Veldkamp \&amp; van der Linden, 2004). This strategy permits substantial improvements in exposure control at little cost to measurement accuracy, However, we do not know whether this option provides better results than using the master bank with greater restriction in the maximum exposure rates (Sympson \&amp; Hetter, 1985). In order to investigate this issue, we worked with several simulated banks of 2100 items, comparing them, for RMSE and overlap rate, with the same banks divided in two, three... up to seven sub-banks. By means of extensive manipulation of the maximum exposure rate in each bank, we found that the option of rotating banks slightly outperformed the option of restricting maximum exposure rate of the master bank by means of the Sympson-Hetter method.</p>
},
	keywords = {*Character, *Databases, *Software Design, Aptitude Tests/*statistics \& numerical data, Bias (Epidemiology), Computing Methodologies, Diagnosis, Computer-Assisted/*statistics \& numerical data, Educational Measurement/*statistics \& numerical data, Humans, Mathematical Computing, Psychometrics/statistics \& numerical data},
	isbn = {1138-7416},
	author = {Barrada, J and Olea, J. and Abad, F. J.}
}
@article {18,
	title = {Methods for restricting maximum exposure rate in computerized adaptative testing},
	journal = {Methodology: European Journal of Research Methods for the Behavioral and Social Sciences},
	volume = {3},
	number = {1},
	year = {2007},
	pages = {14-23},
	publisher = {Hogrefe \& Huber Publishers GmbH: Germany},
	abstract = {The Sympson-Hetter (1985) method provides a means of controlling maximum exposure rate of items in Computerized Adaptive Testing. Through a series of simulations, control parameters are set that mark the probability of administration of an item on being selected. This method presents two main problems: it requires a long computation time for calculating the parameters and the maximum exposure rate is slightly above the fixed limit. Van der Linden (2003) presented two alternatives which appear to solve both of the problems. The impact of these methods in the measurement accuracy has not been tested yet. We show how these methods over-restrict the exposure of some highly discriminating items and, thus, the accuracy is decreased. It also shown that, when the desired maximum exposure rate is near the minimum possible value, these methods offer an empirical maximum exposure rate clearly above the goal. A new method, based on the initial estimation of the probability of administration and the probability of selection of the items with the restricted method (Revuelta \& Ponsoda, 1998), is presented in this paper. It can be used with the Sympson-Hetter method and with the two van der Linden{\textquoteright}s methods. This option, when used with Sympson-Hetter, speeds the convergence of the control parameters without decreasing the accuracy. (PsycINFO Database Record (c) 2007 APA, all rights reserved)},
	keywords = {computerized adaptive testing, item bank security, item exposure control, overlap rate, Sympson-Hetter method},
	isbn = {1614-1881 (Print); 1614-2241 (Electronic)},
	author = {Barrada, J and Olea, J. and Ponsoda, V.}
}
@article {16,
	title = {Maximum information stratification method for controlling item exposure in computerized adaptive testing},
	journal = {Psicothema},
	volume = {18},
	number = {1},
	year = {2006},
	note = {Barrada, Juan RamonMazuela, PalomaOlea, JulioResearch Support, Non-U.S. Gov{\textquoteright}tSpainPsicothemaPsicothema. 2006 Feb;18(1):156-9.},
	month = {Feb},
	pages = {156-159},
	edition = {2007/02/14},
	abstract = {The proposal for increasing the security in Computerized Adaptive Tests that has received most attention in recent years is the a-stratified method (AS - Chang and Ying, 1999): at the beginning of the test only items with low discrimination parameters (a) can be administered, with the values of the a parameters increasing as the test goes on. With this method, distribution of the exposure rates of the items is less skewed, while efficiency is maintained in trait-level estimation. The pseudo-guessing parameter (c), present in the three-parameter logistic model, is considered irrelevant, and is not used in the AS method. The Maximum Information Stratified (MIS) model incorporates the c parameter in the stratification of the bank and in the item-selection rule, improving accuracy by comparison with the AS, for item banks with a and b parameters correlated and uncorrelated. For both kinds of banks, the blocking b methods (Chang, Qian and Ying, 2001) improve the security of the item bank.M{\'e}todo de estratificaci{\'o}n por m{\'a}xima informaci{\'o}n para el control de la exposici{\'o}n en tests adaptativos informatizados. La propuesta para aumentar la seguridad en los tests adaptativos informatizados que ha recibido m{\'a}s atenci{\'o}n en los {\'u}ltimos a{\~n}os ha sido el m{\'e}todo a-estratificado (AE - Chang y Ying, 1999): en los momentos iniciales del test s{\'o}lo pueden administrarse {\'\i}tems con bajos par{\'a}metros de discriminaci{\'o}n (a), increment{\'a}ndose los valores del par{\'a}metro a admisibles seg{\'u}n avanza el test. Con este m{\'e}todo la distribuci{\'o}n de las tasas de exposici{\'o}n de los {\'\i}tems es m{\'a}s equilibrada, manteniendo una adecuada precisi{\'o}n en la medida. El par{\'a}metro de pseudoadivinaci{\'o}n (c), presente en el modelo log{\'\i}stico de tres par{\'a}metros, se supone irrelevante y no se incorpora en el AE. El m{\'e}todo de Estratificaci{\'o}n por M{\'a}xima Informaci{\'o}n (EMI) incorpora el par{\'a}metro c a la estratificaci{\'o}n del banco y a la regla de selecci{\'o}n de {\'\i}tems, mejorando la precisi{\'o}n en comparaci{\'o}n con AE, tanto para bancos donde los par{\'a}metros a y b correlacionan como para bancos donde no. Para ambos tipos de bancos, los m{\'e}todos de bloqueo de b (Chang, Qian y Ying, 2001) mejoran la seguridad del banco.},
	keywords = {*Artificial Intelligence, *Microcomputers, *Psychological Tests, *Software Design, Algorithms, Chi-Square Distribution, Humans, Likelihood Functions},
	isbn = {0214-9915 (Print)},
	author = {Barrada, J and Mazuela, P. and Olea, J.}
}
