Test theory without an answer key

A general model is presented for homogeneous, dichotomous items when the answer key is not known a priori. The model is structurally related to the two-class latent structure model with the roles of respondents and items interchanged. For very small sets of respondents, iterative maximum likelihood estimates of the parameters can be obtained by existing methods. For other situations, new estimation methods are developed and assessed with Monte Carlo data. The answer key can be accurately reconstructed with relatively small sets of respondents. The model is useful when a researcher wants to study objectively the knowledge possessed by members of a culturally coherent group that the researcher is not a member of.This research was supported by NSF Grant No. SES-8320173 to the authors. We gratefully acknowledge comments and suggestions from John Boyd, Tarow Indow, and Kathy Maher as well as the editor and several anonymous referees.     

An availability bias in professional judgment

When branches of a fault tree are pruned, subjects do not fully transfer the probability of those branches to the ‘all other’ category. This underestimation of the catch-all probability has been interpreted as an ‘out of sight, out of mind’ form of the availability bias. The present work replicates this underestimation bias with professional managers. It then demonstrates the effectiveness of a corrective tactic, extending the tree by generating additional causes, and also reveals that more easily retrieved short-term causes dominate the generation process. These results do not differ across managers' culture, education or experience. After evaluating such alternative explanations as category redefinition, we conclude that availability is a major cause, though possibly not the sole cause, of the underestimation bias.     

Discriminability between alternatives in a switching-key concurrent schedule

Six pigeons were trained to discriminate between two intensities of white light in a symbolic matching-to-sample procedure. These stimuli were then used to signal which schedule was available on the main key in a switching-key concurrent schedule. The concurrent schedules led to a symbolic matching-to-sample phase in which the subject identified the concurrent schedule to which it last responded before a reinforcer could be obtained. The concurrent schedules were varied across conditions. Discriminability, measured during the symbolic matching-to-sample performance, was high throughout and did not differ across the two procedures. Performance in the concurrent schedules was like that typically obtained using these schedules. Delays were then arranged between completion of the concurrent schedules and presentations of the symbolic matching-to-sample phase. A series of conditions with an intervening delay of 10 s showed that both concurrent-schedule performance and symbolic matching-to-sample performance were affected by the delay in a similar way; that is, choice responding was closer to indifference.     

Imputation of missing categorical data by maximizing internal consistency

This paper suggests a method to supplant missing categorical data by reasonable replacements. These replacements will maximize the consistency of the completed data as measured by Guttman's squared correlation ratio. The text outlines a solution of the optimization problem, describes relationships with the relevant psychometric theory, and studies some properties of the method in detail. The main result is that the average correlation should be at least 0.50 before the method becomes practical. At that point, the technique gives reasonable results up to 10–15% missing data.We thank Anneke Bloemhoff of NIPG-TNO for compiling and making the Dutch Life Style Survey data available to use, and Chantal Houée and Thérèse Bardaine, IUT, Vannes, France, exchange students under the COMETT program of the EC, for computational assistance. We also thank Donald Rubin, the Editors and several anonymous reviewers for constructive suggestions.     

An automated test development of parallel tests from a seed test

Binary programming models are presented to generate parallel tests from an itembank. The parallel tests are created to match item for item an existing seed test and match user supplied taxonomic specifications. The taxonomic specifications may be either obtained from the seed test or from some other user requirement. An algorithm is presented along with computational results to indicate the overall efficiency of the process. Empirical findings based on an itembank for the Arithmetic Reasoning section of the Armed Services Vocational Aptitude Battery are given.The Office of Naval Research, Program in Cognitive Science, N00014-87-C-0696 partially supported the work of Douglas H. Jones. The Rutgers Research Resource Committee of the Graduate School of Management partially supported the work of Douglas H. Jones and Ing-Long Wu. A Thomas and Betts research fellowship partially supported the work of Ing-Long Wu. The Human Resources Laboratory, United States Air Force, partially supported the work of Ronald Armstrong. The authors benefited from conversations with Dr. Wayne Shore, Operational Technologies, San Antonio, Texas. The order of authors' names is alphabetical and denotes equal authorship.     

Ordinal consistency and ordinal true scores

This paper argues that test data are ordinal, that latent trait scores are only determined ordinally, and that test data are used largely for ordinal purposes. Therefore it is desirable to develop a test theory based only on ordinal assumptions. A set of ordinal assumptions is presented, including an ordinal version of local independence. From these assumptions it is first shown that the gamma-correlation between two tests is the product of their gamma-correlations with the true latent order. The theory is generalized to allow for heterogeneous tests by defining a weighted average local independence. The tau-correlations between total score and the latent order can be found in both homogeneous and heterogeneous cases, and a system of differential item weighting to maximize the tau-correlation between weighted items and the latent order is provided. Thus a purely ordinal test theory seems possible.Part of this work was done while the author was a Visiting Fellow at Macquarrie University. The paper has benefitted from discussions with Professors Thomas J. Reynolds and Roderick P. McDonald and from the comments of several anonymous reviewers.     

Algorithmic shaping and misbehavior in the acquisition of token deposit by rats

In two experiments, rats were trained to deposit ball bearings down a hole in the floor, using an algorithmic version of shaping. The experimenter coded responses expected to be precursors of the target response, ball bearing deposit; a computer program reinforced these responses, or not, according to an algorithm that mimicked the processes thought to occur in conventional shaping. In the first experiment, 8 of 10 rats were successfully shaped; in the second, 5 of 5 were successfully shaped, and the median number of sessions required was the same as for a control group trained using conventional shaping. In both experiments, “misbehavior,” that is, excessive handling and chewing of the ball bearings, was observed, and when the algorithmic shaping procedure was used, misbehavior could be shown to occur in spite of reduced reinforcement for the responses involved.     

Multifactor measurement of bodily feelings: Conceptual development,scale construction,and empirical validation

A series of studies is described demonstrating a coherent exploratory and confirmatory factor-analytic approach to the scaling of self-reported bodily feelings. This approach attempts to optimize the orthogonality, parsimony, and meaningfulness of a multifactor inventory. Psychometric properties of the resulting 35-item Bodily Feeling Scale (BFS) are presented and its comparability with other inventories is discussed. A validity study using item-content-based scales of the Minnesota Multiphasic Personality Inventory showed both concurrent and discriminative validity of the BFS. Implications for clinical and research utility are discussed.Portions of this research were conducted while the first author was supported by a University Graduate Fellowship awarded by the Graduate School of Arts and Sciences at Vanderbilt University.Professor Nunnally passed away in August 1982. His major contributions to the several stages of this research program are recognized through coauthorship.     

A nonparametric approach for assessing latent trait unidimensionality

Assuming a nonparametric family of item response theory models, a theory-based procedure for testing the hypothesis of unidimensionality of the latent space is proposed. The asymptotic distribution of the test statistic is derived assuming unidimensionality, thereby establishing an asymptotically valid statistical test of the unidimensionality of the latent trait. Based upon a new notion of dimensionality, the test is shown to have asymptotic power 1. A 6300 trial Monte Carlo study using published item parameter estimates of widely used standardized tests indicates conservative adherence to the nominal level of significance and statistical power averaging 81 out of 100 rejections for examinee sample sizes and psychological test lengths often incurred in practice.The referees' comments were remarkably detailed and greatly enhanced the writeup and sensitized the author to certain pertinent issues. Discussions with Fritz Drasgow, Lloyd Humphreys, Dennis Jennings, Brian Junker, Robert Linn, Ratna Nandakumar, and Robin Shealy were also very useful.This research was supported by the Office of Naval Research under grant N00014-84-K-0186; NR 150-533, and by the National Science Foundation under grant DMS 85-03321.