Do Student Evaluations of University Reflect Inaccurate Beliefs or Actual Experience? A Relative Rank Model

It was shown that student satisfaction ratings are influenced by context in ways that have important theoretical and practical implications. Using questions from the UK's National Student Survey, the study examined whether and how students' expressed satisfaction with issues such as feedback promptness and instructor enthusiasm depends on the context of comparison (such as possibly inaccurate beliefs about the feedback promptness or enthusiasm experienced at other universities) that is evoked. Experiment 1 found strong effects of experimentally provided comparison context—for example, satisfaction with a given feedback time depended on the time's relative position within a context. Experiment 2 used a novel distribution‐elicitation methodology to determine the prior beliefs of individual students about what happens in universities other than their own. It found that these beliefs vary widely and that students' satisfaction was predicted by how they believed their experience ranked within the distribution of others' experiences. A third study found that relative judgement principles also predicted students' intention to complain. An extended model was developed to show that purely rank‐based principles of judgement can account for findings previously attributed to range effects. It was concluded that satisfaction ratings and quality of provision are different quantities, particularly when the implicit context of comparison includes beliefs about provision at other universities. Quality and satisfaction should be assessed separately, with objective measures (such as actual times to feedback), rather than subjective ratings (such as satisfaction with feedback promptness), being used to measure quality wherever practicable. © 2014 The Authors. Journal of Behavioral Decision Making published by John Wiley & Sons Ltd.     

Intuitive Covariation Assessment of the Illusory Correlation

Most of the research concerned with the illusory correlation is modeled after the seminal work of D. L. Hamilton and R. K. Gifford (1976). However, S. A. Haslam and C. McGarty (1994) have voiced concerns over the dependent measures used within this paradigm. Therefore, in this study, the authors tested a new dependent variable that has high face validity. This measure was modeled after the work of J. R. McGahan and R. Wight (1989) and consisted of a set of propositional statements representing either the illusory correlation, the contingency opposite the illusory correlation, or the noncontingency. A second purpose of this study was to validate other studies that have used dependent measures modeled after the work of J. R. McGahan and R. Wight (1989). Demonstrating that this measure can be used to detect a well-documented phenomenon (i.e., the illusory correlation) would strengthen the results and conclusions from other studies. To this end, results from 2 experiments indicate that this measure does provide a valid alternative to those measures that are commonly used in illusory correlation studies. The results thereby give credence to other studies that have used similar dependent measures.     

Predictors of quality of life enjoyment and satisfaction in individuals living with HIV and AIDS in a resource-constrained setting in South Africa

The burden of HIV disease is concentrated in sub-Saharan Africa, particularly in South Africa (SA). Whilst there have been many studies conducted on the biomedical and socio-psychological aspects of HIV and AIDS, insufficient attention has been paid to the quality of life of those infected with the virus. The primary purpose of the study was to determine the predictors of quality of life enjoyment and satisfaction (Q-LES) among individuals infected with HIV. A battery of questionnaires, which included the Hospital Anxiety and Depression Scale (HADS) and the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), were administered to 121 participants. Data was analysed using SPSS. Of the total sample (n = 121), 74% were females. The study found that a large proportion (49.5%) of the sample within the age group 25–49 years old experienced psychological distress. Those who were not on antiretroviral treatment (ART) were significantly affected (66%). Psychological distress was significantly prevalent among HIV positive individuals and also the strongest predictor of Q-LES among these individuals.     

Intraclass Correlation Associated with Therapists: Estimates and Applications in Planning Psychotherapy Research

It is essential that outcome research permit clear conclusions to be drawn about the efficacy of interventions. The common practice of nesting therapists within conditions can pose important methodological challenges that affect interpretation, particularly if the study is not powered to account for the nested design. An obstacle to the optimal design of these studies is the lack of data about the intraclass correlation coefficient (ICC), which measures the statistical dependencies introduced by nesting. To begin the development of a public database of ICC estimates, the authors investigated ICCs for a variety outcomes reported in 20 psychotherapy outcome studies. The magnitude of the 495 ICC estimates varied widely across measures and studies. The authors provide recommendations regarding how to select and aggregate ICC estimates for power calculations and show how researchers can use ICC estimates to choose the number of patients and therapists that will optimize power. Attention to these recommendations will strengthen the validity of inferences drawn from psychotherapy studies that nest therapists within conditions.     

“Seeing Rain”: Integrating phenomenological and Bayesian predictive coding approaches to visual hallucinations and self-disturbances (Ichstörungen) in schizophrenia

We present a schizophrenia patient who reports “seeing rain” with attendant somatosensory features which separate him from his surroundings. Because visual/multimodal hallucinations are understudied in schizophrenia, we examine a case history to determine the role of these hallucinations in self-disturbances (Ichstörungen). Developed by the early Heidelberg School, self-disturbances comprise two components: 1. The self experiences its own automatic processing as alien to self in a split-off, “doubled-I.” 2. In “I-paralysis,” the disruption to automatic processing is now outside the self in omnipotent agents. Self-disturbances (as indicated by visual/multimodal hallucinations) involve impairment in the ability to predict moment-to-moment experiences in the ongoing perception-action cycle. The phenomenological approach to subjective experience of self-disturbances complements efforts to model psychosis using the computational framework of hierarchical predictive coding. We conclude that self-disturbances play an adaptive, compensatory role following the uncoupling of perception and action, and possibly, other low-level perceptual anomalies.     

The effect of affine transformation on redundancy analysis

Canonical redundancy analysis provides an estimate of the amount of shared variance between two sets of variables and provides an alternative to canonical correlation. The proof that the total redundancy is equal to the average squared multiple correlation coefficient obtained by regressing each variable in the criterion set on all variables in the predictor set is generalized to the case in which there are a larger number of criterion than predictor variables. It is then shown that the redundancy for the criterion set of variables is invariant under affine transformation of the predictor variables, but not invariant under transformation of the criterion variables.     

Multi‐set factor analysis by means of Parafac2

We consider multi‐set data consisting of observations, k = 1,…, K (e.g., subject scores), on J variables in K different samples. We introduce a factor model for the J × J covariance matrices , k = 1,…, K, where the common part is modelled by Parafac2 and the unique variances , k = 1,…, K, are diagonal. The Parafac2 model implies a common loadings matrix that is rescaled for each k, and a common factor correlation matrix. We estimate the unique variances by minimum rank factor analysis on for each k. The factors can be chosen orthogonal or oblique. We present a novel algorithm to estimate the Parafac2 part and demonstrate its performance in a simulation study. Also, we fit our model to a data set in the literature. Our model is easy to estimate and interpret. The unique variances, the factor correlation matrix and the communalities are guaranteed to be proper, and a percentage of explained common variance can be computed for each k. Also, the Parafac2 part is rotationally unique under mild conditions.     

Stochastic pairwise comparative judgements and direct ratings of alternatives in the REMBRANDT system

The REMBRANDT system for multicriteria decision analysis consists of both the multiplicative variant of the AHP (which employs a method of pairwise comparative judgements by a decision maker to arrive at final impact scores for the alternatives under consideration) and SMART, the simple multiattribute rating technique (which utilizes direct rating of alternatives to achieve final impact scores). This paper examines the effect of imprecision or uncertainty in the decision maker's pairwise judgements or ratings of alternatives by expressing each pairwise judgement or rating as a probability distribution, and the structure of REMBRANDT's component models is exploited to derive interval judgements or interval ratings of the alternatives’ final impact scores. These interval judgements or interval ratings can be used to determine the probability of rank reversal amongst alternatives, i.e. to assess the stability of the final impact score vector. © 1998 John Wiley & Sons, Ltd.     

Power Relations and Group Aggregation in the Multiplicative AHP and SMART

The relative power of the members in a group of decision makers can be incorporated in the multiplicative AHP via power coefficients in the logarithmic least squares whereby we analyse the pairwise comparison matrices. When each decision maker judges every pair of alternatives under each of the criteria, aggregation over the criteria and over the decision makers proceeds via a sequence of geometric-mean calculations which can be carried out in any order, at least with predetermined criterion weights and power coefficients. Hence, since we preserve the rank order of the alternatives, we avoid a deficiency of the original AHP. We also consider SMART, an additive method which is logarithmically related to the multiplicative AHP so that power relations can easily be incorporated in it. Finally, in order to illustrate the proposed model, we analyse a generalized version of the well-known example of Belton and Gear as well as the power relations between member countries of the European Community. © 1997 by John Wiley & Sons, Ltd. J. Multi-Crit. Decis. Anal. 6 : 155–165 (1997) No. of Figures: 0. No. of Tables: 6. No. of References: 23.     

Four Covariance Structure Models for Canonical Correlation Analysis: A COSAN Modeling Approach

The mathematical connection between canonical correlation analysis (CCA) and covariance structure analysis was first discussed through the Multiple Indicators and Multiple Causes (MIMIC) approach. However, the MIMIC approach has several technical and practical challenges. To address these challenges, a comprehensive COSAN modeling approach is proposed. Specifically, we define four COSAN-CCA models to correspond with four possible combinations of the data to be analyzed and the unique parameters to be estimated. In terms of the data, one can analyze either the unstandardized or standardized variables. In terms of the unique parameters, one can estimate either the weights or loadings. Besides the unique parameters of each COSAN-CCA model, all four COSAN-CCA models also estimate the canonical correlations as their common parameters. Taken together, the four COSAN-CCA models provide the correct point estimates and standard error estimates for all commonly used CCA parameters. Two numeric examples are used to compare the standard error estimates obtained from the MIMIC approach and the COSAN modeling approach. Moreover, the standard error estimates from the COSAN modeling approach are validated by a simulation study and the asymptotic theory. Finally, software implementation and future extensions are discussed.