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To determine the effects of participation in a low‐impact aerobic exercise program on fatigue, pain, and depression; to examine whether intervention groups compared with a control group differed on functional (grip strength and walk time) and disease activity (total joint count, erythrocyte sedimentation rate, and C‐reactive protein) measures and aerobic fitness at the end of the intervention; and to test which factors predicted exercise participation.A convenience sample of 220 adults with rheumatoid arthritis (RA), ages 40–70, was randomized to 1 of 3 groups: class exercise, home exercise using a videotape, and control group. Measures were obtained at baseline (T1), after 6 weeks of exercise (T2), and after 12 weeks of exercise (T3).Using structural equation modeling, overall symptoms (latent variable for pain, fatigue, and depression) decreased significantly at T3 (P < 0.04) for the class exercise group compared with the control group. There were significant interaction effects of time and group for the functional measures of walk time and grip strength: the treatment groups improved more than the control group (P ≤ 0.005). There were no significant increases in measures of disease activity. Fatigue and perceptions of benefits and barriers to exercise affected participants' amount of exercise, supporting previous research.This study supported the positive effects of exercise on walk time and grip strength, and demonstrated that fatigue and perceived benefits/barriers to exercise influenced exercise participation. Furthermore, overall symptoms of fatigue, pain, and depression were positively influenced in this selective group of patients with RA ages 40–70 years.

The cognitive characteristics of paragraph compre hension items were studied by comparing models that deal with two general processing stages: text represen tation and response decision. The models that were compared included the prepositional structure of the text (Kintsch & van Dijk, 1978), various counts of surface structure variables and word frequency (Drum et al., 1981), a taxonomy of levels of text questions (Anderson, 1972), and some new models that combine features of these models. Calibrations from the linear logistic latent trait model allowed evaluation of the impact of the cognitive variables on item responses. The results indicate that successful prediction of item difficulty is obtained from models with wide represen tation of both text and decision processing. This sug gests that items can be screened for processing diffi culty prior to being administered to examinees. However, the results also have important implications for test validity in that the two processing stages in volve two different ability dimensions.

Four theoretical factor models for a modified Halstead-Reitan battery were formulated, drawing from previous work by Swiercinsky, Royce and co-workers, Christensen and Luria, and Lezak. The relative explanatory power of these four models for this particular battery in an adult neuropsychiatric population was examined using confirmatory factor analysis. None of the models was shown to fit adequately in an absolute sense, but three of them represented substantial, statistically reliable improvements over a null model of mutual independence, and a clear pattern of relative fit was observed. Further improvements were achieved by modifying the best fitting initial model in several ways. A cross-validation with an independent sample supported the results of the model development step. Tentative theoretical and clinical implications for the overall organization of the neuropsychological abilities measured by this battery were drawn, and recommendations were made for further application of this method in neuropsychological research.

Abstract: A latent trait model is presented for the repeated measurement of ability based on a multidimensional conceptualization of the change process. A simplex structure is postulated to link item performance under a given measurement condition or occasion to initial ability and to one or more modifiabilities that represent individual differences in change. Since item discriminations are constrained to be equal within a measurement condition, the model belongs to the family of multidimensional Rasch models. Maximum likelihood estimators of the item parameters and abilities are derived, and an example provided that shows good recovery of both item and ability parameters. Properties of the model are explored, particularly for several classical issues in measuring change.

In many psychological experiments, interaction effects in factorial analysis of variance (ANOVA) designs are often estimated using total scores derived from classical test theory. However, interaction effects can be reduced or eliminated by nonlinear monotonic transformations of a dependent variable. Although cross-over interactions cannot be eliminated by trans formations, the meaningfulness of other interactions hinges on achieving a measurement scale level for which nonlinear transformations are inappropriate (i.e., at least interval scale level). Classical total test scores do not provide interval level measurement according to contemporary item response theory (IRT). Nevertheless, rarely are IRT models applied to achieve more optimal measurement properties and hence more meaningful interaction effects. This paper provides several condi tions under which interaction effects that are estimated from classical total scores, rather than IRT trait scores, can be misleading. Using derived asymptotic expecta tions from an IRT model, interaction effects of zero on the IRT trait scale were often not estimated as zero from the total score scale. Further, when nonzero inter actions were specified on the IRT trait scale, the esti mated interaction effects were biased inward when estimated from the total score scale. Test difficulty level determined both the direction and the magnitude of the biased interaction effects. Index terms: facto rial designs, interaction effects, interval measurement, item response theory, level of measurement, measure ment scales, statistical inference.

Although both general control processing (i.e., global metacomponents) and working memory capacity have emerged as primary explanations of abstract intelligence, their relative impact on individual differences rarely has been compared. This study examines the impact of general control processing and working memory capacity on an important measuring task for abstract intelligence. A new multicomponent latent trait model (MLTM) for covert responses was applied to item response data for matrix problems. With this model, working memory capacity could be separated from general control processing because item processing requirements for the former varies systematically across items (Carpenter, Just, & Shell, 1990), whereas the latter remains constant. Structural equation modeling indicated that both processing abilities were significant sources of individual differences. However, general control processing had a stronger impact. The results, and their limitations, are discussed in the context of prior theory and research.

The Neonatal Behavioral Assessment Scale (NBAS) (Brazelton, 1973, 1984) is a 27-item scale representing individual differences in the newborn infants' behavioral repertoire. The NBAS items are typically collapsed into six clusters (Lester, 1984). Although the NBAS has been examined using exploratory factor analysis methods, no confirmatory factor analysis study has been published in which the behavior structure of full-term, healthy infants is examined. In the current research, competing models assessing variations of the Lester behavior clusters were performed using confirmatory factor analysis. Models comparing six independent factors, six correlated factors, and models estimating a general adaptiveness factor plus six factors were assessed. Examination of the results suggests continued investigations of neonatal behaviors are needed.

Lester (1984) proposed a set of six clusters for the standard 27 items of the National Behavioral Assessment Scale (NBAS). Nine of these items were recorded to change the scale values for the categories. This analysis examined the impact of recording on the psychometric properties of the NBAS. First, correlations were compared between recorded and nonrecorded items within the clusters. Second, iteritem consistencies were computed within each cluster to determine the extent to which the variables measured a common behavioral dimension. Third, a principal components analysis was done to determine the extent to which recoding makes the clusters more distinguishable. The results indicated that the original scale resulted in greater within-cluster correlations and higher interitem consistencies. The recoding method did not result in more distinguisable behavioral clusters. Overall, the original scale provided more optimal psychometric properties.