An alternative to the methodology for analysis of covariance

A general statistical model for simultaneous analysis of data from several groups is described. The model is primarily designed to be used for the analysis of covariance. The model can handle any number of covariates and criterion variables, and any number of treatment groups. Treatment effects may be assessed when the treatment groups are not randomized. In addition, the model allows for measurement errors in the criterion variables as well as in the covariates. A wide variety of hypotheses concerning the parameters of the model can be tested by means of a large sample likelihood ratio test. In particular, the usual assumptions of ANCOVA may be tested.Research reported in this paper has been partly supported by the Swedish Council for Social Science Research under project Statistical methods for analysis of longitudinal data, project director Karl G. Jöreskog, and partly by the Bank of Sweden Tercentenary Foundation under project Structural Equation Models in the Social Sciences, project director Karl G. Jöreskog.     

Spatial and conjoint models based on pairwise comparisons of dissimilarities and combined effects: Complete and incomplete designs

In pairwise multidimensional scaling, a spatial representation for a set of objects is determined from comparisons of the dissimilarity of any two objects drawn from the set to the dissimilarity of other pairs of objects drawn from that set. In pairwise conjoint scaling, comparisons among the joint effects produced by pairs of objects, where the objects in a pair are drawn from separate sets, are used to determine numerical representations for the objects in each set. Monte Carlo simulations of both pairwise dissimilarities and pairwise conjoint effects show that Johnson's algorithm can provide good metric recovery in the presence of high levels of error even when only a small percentage of the complete set of pairwise comparisons are tested.     

EVALUATION OF BIOFEEDBACK IN THE TREATMENT OF BORDERLINE ESSENTIAL HYPERTENSION1

Direct biofeedback of blood pressure was compared with frontal EMG biofeedback and with self-instructed relaxation for the treatment of essential hypertension in a controlled group outcome study. Patients were followed up for four months after the end of treatment. Generalization of treatment effects was assessed through pre- and posttreatment measurements of blood pressure under clinical conditions in a physician's office. There were no significant reductions in diastolic blood pressure. The systolic blood pressure (SBP) of the patients receiving blood pressure biofeedback decreased 8.1 mm mercury (p = 0.07) and the SBP of the patients in the relaxation condition decreased 9.5 mm mercury (p = 0.05). In the generalization measures, there were significant reductions in SBP for the relaxation group. The results are discussed in terms of the general lack of replicability within the area of biofeedback treatment of hypertension.     

Axiomatic and numerical conjoint measurement: An evaluation of diagnostic efficacy

Synthetic data are used to examine how well axiomatic and numerical conjoint measurement methods, individually and comparatively, recover simple polynomial generators in three dimensions. The study illustrates extensions of numerical conjoint measurement (NCM) to identify and model distributive and dual-distributive, in addition to the usual additive, data structures. It was found that while minimum STRESS was the criterion of fit, another statistic, predictive capability, provided a better diagnosis of the known generating model. That NCM methods were able to better identify generating models conflicts with Krantz and Tversky's assertion that, in general, the direct axiom tests provide a more powerful diagnostic test between alternative composition rules than does evaluation of numerical correspondence. For all methods, dual-distributive models are most difficult to recover, while consistent with past studies, the additive model is the most robust of the fitted models.Douglas Emery is now at the Krannert Graduate School of Management, Purdue University, West Lafayette, IN, on leave from the University of Calgary.     

The use of teachers as behavioral observers

The effect of using teachers as behavioral observers on both student and teacher behavior was examined with eight teachers and 32 elementary school children. The frequency of prompts (but not praise or criticism) to those students observed by the teacher increased significantly from nonobserver to teacher observed experimental phases. In addition, students observed by the teacher showed more change in appropriate behavior than students who were not observed. The significance of these findings for research and therapy is discussed.     

Considerations in the choice of interobserver reliability estimates

Two types of interobserver reliability values may be needed in treatment studies in which observers constitute the primary data-acquisition system: trial reliability and the reliability of the composite unit or score which is subsequently analyzed, e.g., daily or weekly session totals. Two approaches to determining interobserver reliability are described: percentage agreement and "correlational" measures of reliability. The interpretation of these estimates, factors affecting their magnitude, and the advantages and limitations of each approach are presented.     

THE ROLE OF FEEDBACK IN VOLUNTARY CONTROL OF BLOOD PRESSURE IN INSTRUCTED SUBJECTS1

Forty normal male volunteers were randomly assigned to one of four experimental conditions and instructed to raise and lower their systolic blood pressure. Subjects received either beat-to-beat feedback contingent on pressure changes, noncontingent beat-to-beat feedback, noncontingent feedback presented randomly with respect to the occurrence of each heart beat, or instructions alone. The order of increase and decrease trial blocks was counterbalanced across groups. Subjects receiving contingent feedback were monetarily rewarded for appropriate pressure changes. Subjects receiving noncontingent feedback received rewards and feedback equal to the mean received by the contingent group. Subjects in the instructions-only condition were also paid this bonus but were informed of their earnings only at the conclusion of the experiment. Results indicated that in the presence of instructions, feedback, whether contingent or noncontingent, added little to subjects' ability to control pressure during a single session. Theoretical and clinical implications are discussed.     

Correlation and prediction in ordinal test theory

Based on the test theory model for ordinal measurements proposed by Schulman and Haden, the present paper considers correlations between tests, attenuation, regressions involving true and observed scores, and prediction of test reliability.The population correlation between tests is shown to be related to the expected sample correlation for samples of sizen ₁ andn ₂. Errors of estimation, measurement and prediction are found to be similar to their counterparts in interval test theory, while attenuation is identical to its counterpart. The bias in estimating population reliability from sample data is compared for Kendall's tau and Spearman's rho.The author wishes to thank the referees for their helpful comments on an earlier draft of this paper, and in particular, for the suggested alternative methods of establishing some of the presented results.