On Using Stochastic Curtailment to Shorten the SPRT in Sequential Mastery Testing

Matthew Finkelman

41 citations0/0 files storedJournal of Educational and Behavioral Statistics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Psychometric Methodologies and Testing Statistical Methods in Clinical Trials Educational Technology and Assessment

Abstract

Sequential mastery testing (SMT) has been researched as an efficient alternative to paper-and-pencil testing for pass/fail examinations. One popular method for determining when to cease examination in SMT is the truncated sequential probability ratio test (TSPRT). This article introduces the application of stochastic curtailment in SMT to shorten the TSPRT without substantially compromising error rates. Unlike the TSPRT, the stochastically curtailed procedure exhibits an optimality property known as weak admissibility. Error bounds of the two methods are provided in terms of one another. In two simulation sets, the stochastically curtailed procedure considerably improved the average test length of an SMT with only a slight decrease in accuracy.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 41 citations exist upstream.

References

1969Statistical Theories of Mental Test Scores 2012Applications of Item Response Theory To Practical Testing Problems 1968Some latent trait models and their use in inferring an examinee's ability 1985Sequential Analysis 1989Procedures for Selecting Items for Computerized Adaptive Tests 1998Controlling Item Exposure Conditional on Ability in Computerized Adaptive Testing 1999Item Selection in Adaptive Testing with the Sequential Probability Ratio Test 1996Comparison of SPRT and Sequential Bayes Procedures for Classifying Examinees Into Two Categories Using a Computerized Test

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.