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Comparison of SPRT and Sequential Bayes Procedures for Classifying Examinees Into Two Categories Using a Computerized Test

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Keywords: classification, computerized testing, sequential Bayes, sequential probability ratio test Many testing applications focus on classifying examinees into one of two categories (e.g., pass/fail) rather than on obtaining an accurate estimate of level of ability. Examples of such applications include licensure and certification, college selection, and placement into entry-level or developmental college courses. With the increased availability of computers for the administration and scoring of tests, computerized testing procedures have been developed for efficiently making these classification decisions. The purpose of the research reported in this article was to compare two such procedures, one based on the sequential probability ratio test and the other on sequential Bayes methodology, to determine which required fewer items for classification when the procedures were matched on classification error rates. The results showed that under the conditions studied, the SPRT procedure required fewer test items than the sequential Bayes procedure to achieve the same level of classification accuracy. Two methods that have been proposed to classify examinees into two categories (e.g., pass versus fail) using computerized testing are the sequential probability ratio test, or SPRT (Ferguson, 1969a, 1969b; Reckase, 1983; Wald, 1947), and a procedure based on sequential Bayes estimates of an examinee's latent trait or ability (Kingsbury & Weiss, 1983). The latter will be referred to in this article as the sequential Bayes procedure, or SB. Both methods focus on the administration of single test items rather than blocks of test items, sometimes referred to as testlets (Lewis & Sheehan, 1990; Sheehan & Lewis, 1992). The testlet-based technique will not be discussed in the present article. It is difficult to compare the two procedures head-to-head primarily due to the difficulty in matching or equating the two procedures so that comparisons are meaningful. Both the SPRT and SB procedures require certain, but different, test characteristics or parameters to be established prior to testing. However, both procedures yield similar outcome measures that are comparable. For example, both procedures classify an examinee with some latent ability into one of two mutually exclusive categories with a certain degree of accuracy following the administration of an expected number of test items.' This content downloaded from 35.8.11.3 on Sat, 29 Nov 2014 15:41:47 PM All use subject to JSTOR Terms and Conditions Spray and Reckase In order to compare SPRT and SB, it should be possible to match or equate the two procedures on one of the outcomes, such as classification error, and then observe which procedure demonstrates classification with fewer test items. (Note that it would be just as logical and perhaps more important to match on the expected number of test items and then observe classification rates to determine which technique produces fewer classification errors. However, that is a more difficult task.) One attempt to compare the two procedures was reported by Kingsbury and Weiss (1983). Their results tended to favor the SB procedure over the SPRT. Several factors, important in computerized classification testing situations, were considered in this study. Maximum test length varied from 10 to 50 items, and the composition of the item pool was varied by changing the values of the item parameters. Results were also compared to those from conventional tests. The results seemed to indicate that the SB procedure was more efficient than the SPRT procedure. However, Kingsbury and Weiss admitted that they had not actually been able to match the procedures in any statistical sense, so that their results never provided a formal comparison of the two testing techniques. Wald (1947) showed analytically that the SPRT was the uniformly

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Comparison of SPRT and Sequential Bayes Procedures for Classifying Examinees into Two
Categories Using a Computerized Test
Author(s): Judith A. Spray and Mark D. Reckase
Source: Journal of Educational and Behavioral Statistics, Vol. 21, No. 4 (Winter, 1996), pp.
405-414
Published by: American Educational Research Association and American Statistical Association
Stable URL: http://www.jstor.org/stable/1165342 .
Accessed: 29/11/2014 15:41

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, Journal of Educational and Behavioral Statistics
Winter 1996, Vol. 21, No. 4, pp. 405-414




Comparison of SPRT and Sequential Bayes
Procedures for Classifying Examinees Into Two
Categories Using a ComputerizedTest
Judith A. Spray and Mark D. Reckase
American College Testing

Keywords:classification,computerized
testing,sequentialBayes,sequentialprobabil-
ity ratio test

Many testingapplicationsfocus on classifyingexamineesinto one of two
categories(e.g., pass/fail) ratherthan on obtainingan accurate estimate
of level of ability. Examplesof such applicationsinclude licensureand
certification,college selection,and placementinto entry-levelor develop-
mentalcollege courses.Withthe increasedavailabilityof computersfor the
administrationand scoring of tests, computerizedtestingprocedureshave
been developedfor efficientlymakingthese classificationdecisions. The
purposeof the researchreportedin this article was to comparetwo such
procedures,one basedon the sequentialprobabilityratio test and the other
on sequentialBayesmethodology,to determinewhichrequiredfewer items
for classificationwhentheprocedureswerematchedon classificationerror
rates. The results showed that under the conditionsstudied, the SPRT
procedurerequired fewer test itemsthanthe sequentialBayesprocedureto
achieve the same level of classificationaccuracy.

Two methods that have been proposedto classify examinees into two
categories(e.g., passversusfail) usingcomputerized testingarethe sequential
probability ratio test, or SPRT (Ferguson,1969a, 1969b; Reckase, 1983;
Wald, 1947), and a procedurebased on sequentialBayes estimatesof an
examinee'slatenttraitor ability(Kingsbury& Weiss, 1983). The latterwill
be referredto in this articleas the sequentialBayes procedure,or SB. Both
methodsfocus on the administration of single test items ratherthanblocks
of test items, sometimesreferredto as testlets (Lewis & Sheehan, 1990;
Sheehan& Lewis, 1992). The testlet-basedtechniquewill not be discussed
in the presentarticle.
It is difficultto comparethe two procedureshead-to-headprimarilydue
to the difficultyin matchingor equatingthe two proceduresso thatcompari-
sons are meaningful.Both the SPRTand SB proceduresrequirecertain,but
different,test characteristics or parametersto be establishedpriorto testing.
However,bothproceduresyield similaroutcomemeasuresthatarecompara-
ble. For example, both proceduresclassify an examinee with some latent
ability into one of two mutuallyexclusive categorieswith a certaindegree
of accuracyfollowingtheadministration of anexpectednumberof testitems.'




This content downloaded from 35.8.11.3 on Sat, 29 Nov 2014 15:41:47 PM
All use subject to JSTOR Terms and Conditions

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