@article {2332, title = {Enhancing Pool Utilization in Constructing the Multistage Test Using Mixed-Format Tests}, journal = {Applied Psychological Measurement}, volume = {38}, number = {4}, year = {2014}, pages = {268-280}, abstract = {

This study investigated a new pool utilization method of constructing multistage tests (MST) using the mixed-format test based on the generalized partial credit model (GPCM). MST simulations of a classification test were performed to evaluate the MST design. A linear programming (LP) model was applied to perform MST reassemblies based on the initial MST construction. Three subsequent MST reassemblies were performed. For each reassembly, three test unit replacement ratios (TRRs; 0.22, 0.44, and 0.66) were investigated. The conditions of the three passing rates (30\%, 50\%, and 70\%) were also considered in the classification testing. The results demonstrated that various MST reassembly conditions increased the overall pool utilization rates, while maintaining the desired MST construction. All MST testing conditions performed equally well in terms of the precision of the classification decision.

}, doi = {10.1177/0146621613515545}, url = {http://apm.sagepub.com/content/38/4/268.abstract}, author = {Park, Ryoungsun and Kim, Jiseon and Chung, Hyewon and Dodd, Barbara G.} } @article {2304, title = {A Comparison of Exposure Control Procedures in CATs Using the 3PL Model}, journal = {Educational and Psychological Measurement}, volume = {73}, number = {5}, year = {2013}, pages = {857-874}, abstract = {

This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson\–Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the manipulated conditions of item pool size (small vs. large) and stopping rules (fixed-length vs. variable-length). PR-SE provides the advantage of similar constraints to SH, without the need for a preceding simulation study to execute it. Overall for the large and small item banks, the PR-SE method administered almost all of the items from the item pool, whereas the other procedures administered about 52\% or less of the large item bank and 80\% or less of the small item bank. The PR-SE yielded the smallest amount of item overlap between tests across conditions and administered fewer items on average than SH. PR-SE obtained these results with similar, and acceptable, measurement precision compared to the other exposure control procedures while vastly improving on item pool usage.

}, doi = {10.1177/0013164413486802}, url = {http://epm.sagepub.com/content/73/5/857.abstract}, author = {Leroux, Audrey J. and Lopez, Myriam and Hembry, Ian and Dodd, Barbara G.} } @article {2212, title = {Balancing Flexible Constraints and Measurement Precision in Computerized Adaptive Testing}, journal = {Educational and Psychological Measurement}, volume = {72}, number = {4}, year = {2012}, pages = {629-648}, abstract = {

Managing test specifications\—both multiple nonstatistical constraints and flexibly defined constraints\—has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT, and the weighted penalty model in balancing multiple flexible constraints and maximizing measurement precision in a fixed-length CAT. The study also addressed the effect of two different test lengths\—25 items and 50 items\—and of including or excluding the randomesque item exposure control procedure with the three methods, all of which were found effective in selecting items that met flexible test constraints when used in the item selection process for longer tests. When the randomesque method was included to control for item exposure, the weighted penalty model and the flexible modified constrained CAT models performed better than did the constrained CAT procedure in maintaining measurement precision. When no item exposure control method was used in the item selection process, no practical difference was found in the measurement precision of each balancing method.

}, doi = {10.1177/0013164411431838}, url = {http://epm.sagepub.com/content/72/4/629.abstract}, author = {Moyer, Eric L. and Galindo, Jennifer L. and Dodd, Barbara G.} } @article {2193, title = {Comparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model}, journal = {Educational and Psychological Measurement}, volume = {72}, number = {1}, year = {2012}, pages = {159-175}, abstract = {

This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability distributions (normally distributed and negatively skewed data), and three exposure control procedures (randomesque procedure, progressive\–restricted procedure, and maximum information procedure). A number of measurement precision indexes such as descriptive statistics, correlations between known and estimated ability levels, bias, root mean squared error, and average absolute difference, exposure rates, item usage, and item overlap were computed to assess the impact of matched or nonmatched item pool and ability distributions on the accuracy of ability estimation and the performance of exposure control procedures. As expected, the medium item pool produced better precision of measurement than both the easy and hard item pools. The progressive\–restricted procedure performed better in terms of maximum exposure rates, item average overlap, and pool utilization than both the randomesque procedure and the maximum information procedure. The easy item pool with the negatively skewed data as a mismatched condition produced the worst performance.

}, doi = {10.1177/0013164411411296}, url = {http://epm.sagepub.com/content/72/1/159.abstract}, author = {Lee, HwaYoung and Dodd, Barbara G.} } @article {2279, title = {Item Selection and Ability Estimation Procedures for a Mixed-Format Adaptive Test}, journal = {Applied Measurement in Education}, volume = {25}, number = {4}, year = {2012}, pages = {305-326}, doi = {10.1080/08957347.2012.714686}, url = {http://www.tandfonline.com/doi/abs/10.1080/08957347.2012.714686}, author = {Ho, Tsung-Han and Dodd, Barbara G.} } @article {2211, title = {Panel Design Variations in the Multistage Test Using the Mixed-Format Tests}, journal = {Educational and Psychological Measurement}, volume = {72}, number = {4}, year = {2012}, pages = {574-588}, abstract = {

This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized adaptive test (CAT) conditions provided baseline comparisons. Three passing rate conditions were also included. The various MST conditions using mixed-format tests were constructed properly and performed well. When the levels of TIFs at the first stage were higher, the simulations produced a greater number of correct classifications. CAT with the randomesque-10 procedure yielded comparable results to the MST with increased levels of TIFs. Finally, all MST conditions achieved better test security results compared with CAT\’s maximum information conditions.

}, doi = {10.1177/0013164411428977}, url = {http://epm.sagepub.com/content/72/4/574.abstract}, author = {Kim, Jiseon and Chung, Hyewon and Dodd, Barbara G. and Park, Ryoungsun} } @article {2189, title = {A New Stopping Rule for Computerized Adaptive Testing}, journal = {Educational and Psychological Measurement}, volume = {71}, number = {1}, year = {2011}, pages = {37-53}, abstract = {

The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant.

}, doi = {10.1177/0013164410387338}, url = {http://epm.sagepub.com/content/71/1/37.abstract}, author = {Choi, Seung W. and Grady, Matthew W. and Dodd, Barbara G.} } @article {2161, title = {A Comparison of Item Selection Techniques for Testlets}, journal = {Applied Psychological Measurement}, volume = {34}, number = {6}, year = {2010}, pages = {424-437}, abstract = {

This study examined the performance of the maximum Fisher\’s information, the maximum posterior weighted information, and the minimum expected posterior variance methods for selecting items in a computerized adaptive testing system when the items were grouped in testlets. A simulation study compared the efficiency of ability estimation among the item selection techniques under varying conditions of local-item dependency when the response model was either the three-parameter-logistic item response theory or the three-parameter-logistic testlet response theory. The item selection techniques performed similarly within any particular condition, the practical implications of which are discussed within the article.

}, doi = {10.1177/0146621609349804}, url = {http://apm.sagepub.com/content/34/6/424.abstract}, author = {Murphy, Daniel L. and Dodd, Barbara G. and Vaughn, Brandon K.} } @article {2143, title = {Computerized Adaptive Testing With the Partial Credit Model: Estimation Procedures, Population Distributions, and Item Pool Characteristics}, journal = {Applied Psychological Measurement}, volume = {29}, number = {6}, year = {2005}, pages = {433-456}, abstract = {

The primary purpose of this research is to examine the impact of estimation methods, actual latent trait distributions, and item pool characteristics on the performance of a simulated computerized adaptive testing (CAT) system. In this study, three estimation procedures are compared for accuracy of estimation: maximum likelihood estimation (MLE), expected a priori (EAP), and Warm\&$\#$39;s weighted likelihood estimation (WLE). Some research has shown that MLE and EAP perform equally well under certain conditions in polytomous CAT systems, such that they match the actual latent trait distribution. However, little research has compared these methods when prior estimates of. distributions are extremely poor. In general, it appears that MLE, EAP, and WLE procedures perform equally well when using an optimal item pool. However, the use of EAP procedures may be advantageous under nonoptimal testing conditions when the item pool is not appropriately matched to the examinees.

}, doi = {10.1177/0146621605280072}, url = {http://apm.sagepub.com/content/29/6/433.abstract}, author = {Gorin, Joanna S. and Dodd, Barbara G. and Fitzpatrick, Steven J. and Shieh, Yann Yann} }