Fluency versus conscious recollection in the word completion performance of amnesic patients

To examine the relative contribution of fluency and recollection to the word completion performance of amnesics, we administered a task in which patients were told specifically not to utilize previously presented words during stem completion (an Exclusion condition). This condition was contrasted with a standard word completion task in which patients were encouraged simply to complete the stem with the first word that came to mind (an Inclusion condition). Since the exclusion condition necessitated controlled respecification of the initial presentation, it was hypothesized that amnesics would be less able than controls to exclude study list items. Consistent with this hypothesis, the results indicated that the amnesics' performance, unlike that of the alcoholic controls, did not significantly differ as a function of task condition. To examine whether amnesics' conscious recollection could be enhanced, Experiment 2 presented the study list five times. The amnesics now were able to exclude a significant number of items from the study list; however, they still did so considerably less frequently than alcoholic controls. For the alcoholic controls, increasing the number of study trials had little additional effect on their exclusion performance, but it significantly enhanced their inclusion performance. Taken together, these findings suggest that for control subjects, word completion performance is likely mediated by a combination of fluency and recollection, while for amnesic patients, performance is almost exclusively based on the fluency with which an item comes to mind.     

Reliability of test scores in nonparametric item response theory

Three methods for estimating reliability are studied within the context of nonparametric item response theory. Two were proposed originally by Mokken (1971) and a third is developed in this paper. Using a Monte Carlo strategy, these three estimation methods are compared with four classical lower bounds to reliability. Finally, recommendations are given concerning the use of these estimation methods.The authors are grateful for constructive comments from the reviewers and from Charles Lewis.     

Rehearsal strategy as a function of recall expectation

The subjects were divided into three groups with respect to their expectations concerning a recall task given after the final trial of the usual STM distractor procedure. Group 1 were told only that they would have to recall during each trial's recall interval, thus did not expect to have to recall again. Group 2 were told that they would have to recall all the words presented in the experiment at the end of the last trial, in addition to the trial-by-trial recall. Group 3 were told only that they would have to recall after all words had been presented and they sat passively through the presentation trials. In addition to their recall expectations, half of the subjects in each group received a 2-s presentation and half received a 5-s presentation interval. It was found that the length of the presentation interval had an effect on the number of words recalled at the end of all trials, but recall expectancy did not. However, expectancy did determine the rehearsal strategies of subjects and hence the serial positions from which items were recalled.     

The many null distributions of person fit indices

This paper deals with the situation of an investigator who has collected the scores ofn persons to a set ofk dichotomous items, and wants to investigate whether the answers of all respondents are compatible with the one parameter logistic test model of Rasch. Contrary to the standard analysis of the Rasch model, where all persons are kept in the analysis and badly fittingitems may be removed, this paper studies the alternative model in which a small minority ofpersons has an answer strategy not described by the Rasch model. Such persons are called anomalous or aberrant. From the response vectors consisting ofk symbols each equal to 0 or 1, it is desired to classify each respondent as either anomalous or as conforming to the model. As this model is probabilistic, such a classification will possibly involve false positives and false negatives. Both for the Rasch model and for other item response models, the literature contains several proposals for a person fit index, which expresses for each individual the plausibility that his/her behavior follows the model. The present paper argues that such indices can only provide a satisfactory solution to the classification problem if their statistical distribution is known under the null hypothesis that all persons answer according to the model. This distribution, however, turns out to be rather different for different values of the person's latent trait value. This value will be called ability parameter, although our results are equally valid for Rasch scales measuring other attributes.As the true ability parameter is unknown, one can only use its estimate in order to obtain an estimated person fit value and an estimated null hypothesis distribution. The paper describes three specifications for the latter: assuming that the true ability equals its estimate, integrating across the ability distribution assumed for the population, and conditioning on the total score, which is in the Rasch model the sufficient statistic for the ability parameter.Classification rules for aberrance will be worked out for each of the three specifications. Depending on test length, item parameters and desired accuracy, they are based on the exact distribution, its Monte Carlo estimate and a new and promising approximation based on the moments of the person fit statistic. Results for the likelihood person fit statistic are given in detail, the methods could also be applied to other fit statistics. A comparison of the three specifications results in the recommendation to condition on the total score, as this avoids some problems of interpretation that affect the other two specifications.The authors express their gratitude to the reviewers and to many colleagues for comments on an earlier version.     

Stochastic ordering using the latent trait and the sum score in polytomous IRT models

In a restricted class of item response theory (IRT) models for polytomous items the unweighted total score has monotone likelihood ratio (MLR) in the latent trait. MLR implies two stochastic ordering (SO) properties, denoted SOM and SOL, which are both weaker than MLR, but very useful for measurement with IRT models. Therefore, these SO properties are investigated for a broader class of IRT models for which the MLR property does not hold.In this study, first a taxonomy is given for nonparametric and parametric models for polytomous items based on the hierarchical relationship between the models. Next, it is investigated which models have the MLR property and which have the SO properties. It is shown that all models in the taxonomy possess the SOM property. However, counterexamples illustrate that many models do not, in general, possess the even more useful SOL property.Hemker's research was supported by the Netherlands Research Council, Grant 575-67-034. Junker's research was supported in part by the National Institutes of Health, Grant CA54852, and by the National Science Foundation, Grant DMS-94.04438.     

An extension of the partial credit model with an application to the measurement of change

The partial credit model is considered under the assumption of a certain linear decomposition of the item × category parameters _ih into basic parameters _j. This model is referred to as the linear partial credit model. A conditional maximum likelihood algorithm for estimation of the j is presented, based on (a) recurrences for the combinatorial functions involved, and (b) using a quasi-Newton approach, the so-called Broyden-Fletcher-Goldfarb-Shanno (BFGS) method; (a) guarantees numerically stable results, (b) avoids the direct computation of the Hesse matrix, yet produces a sequence of certain positive definite matricesB _k ,k=1, 2, ..., converging to the asymptotic variance-covariance matrix of the . The practicality of these numerical methods is demonstrated both by means of simulations and of an empirical application to the measurement of treatment effects in patients with psychosomatic disorders.The authors thank one anonymous reviewer for his constructive comments. Moreover, they thankfully acknowledge financial support by the Österreichische Nationalbank (Austrian National Bank) under Grant No. 3720.     

Treatment of obsessive-compulsive patients: The contribution of self-instructional training to the effectiveness of exposure

Fifteen obsessive-compulsive patients were given treatment consisting of ten sessions of gradual exposure in vivo. For half of the patients gradual exposure in vivo was preceded by self-instructional training.Treatment resulted in significant improvement on anxiety and avoidance scales, Leyton Obsessional Inventory, Self-rating Depression Scale and on ratings for anxious mood and depression. Neither the post-test nor the follow-ups 1 month and 6 months later indicated a difference between the effects of the two conditions. Self-instructional training did not enhance the effectiveness of gradual exposure in vivo.     

Exploring Human Values in the Design of a Web-Based QoL-Instrument for People with Mental Health Problems: A Value Sensitive Design Approach

Science and Engineering Ethics - Quality of life (QoL) is an important outcome measure in mental health care. Currently, QoL is mainly measured with paper and pencil questionnaires. To contribute...     

A person-fit index for polytomous rasch models,latent class models,and their mixture generalizations

A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data.This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch model to a number of models for categorical data. A comparison of two different approaches to handle the skewness of the person-fit index distribution is included.Major parts of this paper were written while the first author worked at the Institute for Science Education, Kiel, Germany. Any opinions expressed in this paper are those of the authors and not necessarily of Educational Testing Service. The results presented in this paper were improved by valuable comments from J. Rost, K. Yamamoto, N.D. Verhelst, E. Bedrick and two anonymous reviewers.