Testing a unidimensional,qualitative unfolding model for attitudinal or developmental data

Assuming that subject responses rank order stimuli by preference, statistical methods are presented for testing the hypothesis that responses conform to a unidimensional, qualitative unfolding model and to an a priori stimulus ordering. The model postulates that persons and stimulus variables are ordered along a single continuum and that subjects most prefer stimuli nearest their own position. The underlying continuum need not form an interval scale of the stimulus attribute. The general assumptions of the test for the unfolding model make it suitable for the analysis of structure in attitude responses, preference data, and developmental stage data.This research was supported by a grant from the U.S. Public Health Service (Grant No. 1-R01-MH27861-01) to the University of Minnesota. I wish to thank Sanford Weisberg for his helpful suggestions. I also wish to thank Karen Kitchener and Patricia King for letting me use their data.     

Fitting and testing carroll's weighted unfolding model for preferences

A quadratic programming algorithm is presented for fitting Carroll's weighted unfolding model for preferences to known multidimensional scale values. The algorithm can be applied directly to pairwise preferences; it permits nonnegativity constraints on subject weights; and it provides a means of testing various preference model hypotheses. While basically metric, it can be combined with Kruskal's monotone regression to fit ordinal data. Monte Carlo results show that (a) adequacy of true preference recovery depends on the number of data points and the amount of error, and (b) the proportion of data variance accounted for by the model sometimes only approximately reflects true recovery.This study is based on a doctoral dissertation submitted to the University of Illinois at Urbana-Champaign. The author wishes to thank the members of his dissertation committee—Lawrence E. Jones, Chairman, Charles Lewis, Stephen Golding, Ledyard Tucker, and Nancy Wiggins—for their helpful comments.     

On the Psychological Significance of the Euclidean Representation of Implicit Personality Theory

The overall purpose of the present study was to investigate the psychological significance of the Euclidean representation of implicit personality theory (IPT) by testing the predictive usefulness of this representation. Multidimensional scaling analyses of 18 subjects' estimates of assumed trait co-occurences (IPT) gave Euclidean trait-distance matrices which were used to predict the subjects' trait-to-trait inferences. The results showed that: (1) The Euclidean representations of subjects' IPTs can be used to predict ( p < 0.10) most subjects' (14 of 18) trait-to-trait inferences; (2) The similarity between the Euclidean representation of subjects' IPTs was positively correlated (r_s = 0.43, p < 0.001) with the similarity between subjects' trait-to-trait inferences. These results suggest that the Euclidean representation of IPT has some predictive value, and thus, may at least to some extent, be justified and considered as psychologically significant.     

The relationship among the transtheoretical model of behavioral change,psychological distress,and diet attitudes in obesity: Implications for primary care intervention

Obesity is prevalent but undertreated in primary care. Family practice volunteer outpatients (N=454) were administered the Stage of Change for Weight (URICA), the Brief Symptom Inventory (BSI), and the Diet Readiness Test (DRT) to assess the relationship between these variables and obesity. The body mass index (BMI) was used to classify obesity revealing 197 patients with elevated BMI's. There was no significant difference between the obese and the nonobese on any of the psychological measures. The obese reported significantly more difficulty setting diet goals and less control over their eating, ate more to emotional situations, and exercised less than the nonobese. The obese sample (46.7%) reported being in the Action stage of change for weight management. Implications for intervention in primary care include targeting attitudes (DRT) and dispelling physician attitudes that obese individuals have increased levels of psychological distress. Addressing Stage of Change for weight management can facilitate tailoring the appropriate intervention when used in concert with the DRT variables.     

Describing the elephant: Structure and function in multivariate data

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain.     

An analysis and synthesis of multiple correspondence analysis,optimal scaling,dual scaling,homogeneity analysis and other methods for quantifying categorical multivariate data

We discuss a variety of methods for quantifying categorical multivariate data. These methods have been proposed in many different countries, by many different authors, under many different names. In the first major section of the paper we analyze the many different methods and show that they all lead to the same equations for analyzing the same data. In the second major section of the paper we introduce the notion of a duality diagram, and use this diagram to synthesize the many superficially different methods into a single method.The ideas in this paper were worked out by the first author, with some suggestions provided by the second. The current version of this paper has evolved from three previous versions, the first two written by the first author.     

Personality Traits, Partisan Attitudes, and Voting Behavior. Evidence from Germany

Political psychology has paid rather little attention to personality traits when explaining political attitudes and political behavior in mass publics. The present paper argues that personality traits contribute to our understanding of political attitude formation and decision making of ordinary citizens. Based on the Five Factor Model of Personality, we state hypotheses regarding the effects of personality traits on partisan attitudes and vote choice in Germany. We test the hypotheses using survey data obtained from a random sample of the Germans eligible to vote. The evidence confirms that personality traits indirectly affect partisan attitudes and voting behavior in Germany in predictable ways even after controlling for sociodemographic characteristics. More specifically, Openness makes citizens more inclined to support parties endorsing social liberalism whereas low scores on Conscientiousness increase the likelihood of liking and voting for parties subscribing to economic or social liberalism as do high levels on Agreeableness . High levels of Neuroticism appear to promote support for parties that offer shelter against material or cultural challenges.     

Estimation for the multiple factor model when data are missing

A maximum likelihood method of estimating the parameters of the multiple factor model when data are missing from the sample is presented. A Monte Carlo study compares the method with 5 heuristic methods of dealing with the problem. The present method shows some advantage in accuracy of estimation over the heuristic methods but is considerably more costly computationally.This paper is based on the author's doctoral dissertation at the Department of Psychology, University of Illinois at Urbana-Champaign. The author gratefully acknowledges the aid of Drs. Robert Bohrer, Charles Lewis, Robert Linn, Maurice Tatsuoka, and Ledyard Tucker.     

Decomposition,Interdependence and Precision in Multiattribute Utility Measurements

Traditionally, parameters of multiattribute utility models, representing a decision maker's preference judgements, are treated deterministically. This may be unrealistic, because assessment of such parameters is potentially fraught with imprecisions and errors. We thus treat such parameters as stochastic and investigate how their associated imprecision/errors are propagated in an additive multiattribute utility function in terms of the aggregate variance. Both a no information and a rank order case regarding the attribute weights are considered, assuming a uniform distribution over the feasible region of attribute weights constrained by the respective information assumption. In general, as the number of attributes increases, the variance of the aggregate utility in both cases decreases and approaches the same limit, which depends only on the variances as well as the correlations among the single-attribute utilities. However, the marginal change in aggregate utility variance decreases rather rapidly and hence decomposition as a variance reduction mechanism is generally useful but becomes relatively ineffective if the number of attributes exceed about 10. Moreover, it was found that utilities which are positively correlated increase the aggregate utility variance, hence every effort should be made to avoid positive correlations between the single-attribute utilities. We also provide guidelines for determining under what condition and to what extent a decision maker should decompose to obtain an aggregate utility variance that is smaller than that of holistic assessments. Extensions of the current model and empirical research to support some of our behavioural assumptions are discussed. © 1997 John Wiley & Sons, Ltd.     

Measuring decentering as a unidimensional construct: The development and initial validation of the Decentering Scale for Sport

Decentering, the ability to observe one's thoughts and feelings from a detached view, has gained increased attention in recent years. With this renewed interest comes a need for a reliable and valid tool to measure decentering in sport contexts. Therefore, in this multi-study paper we report the development and initial validation of a sport-specific self-report measure of decentering, the Decentering Scale for Sport (DSS). Based on an initial pool of context-specific items with acceptable content validity, a unidimensional decentering construct was confirmed in four independent athletic samples (n = 1255). Satisfactory internal consistency reliability and partial measurement invariance across gender and sport type was demonstrated. Convergent and concurrent validity of the DSS was established by showing positive and medium to large associations with mindfulness, well-being, flow, vitality, enjoyment and positive affect, and negative and medium to large associations with cognitive fusion, experiential avoidance, anxiety and negative affect. Discriminant validity of decentering with mindfulness and self-compassion was also established. Findings suggest that the DSS is a reliable and valid measure of decentering in sport contexts, and can be applied in future research and applied practice to measure decentering.     

A distance-based variety of nonlinear multivariate data analysis, including weights for objects and variables

In the distance approach to nonlinear multivariate data analysis the focus is on the optimal representation of the relationships between the objects in the analysis. In this paper two methods are presented for including weights in distance-based nonlinear multivariate data analysis. In the first method, weights are assigned to the objects while the second method is concerned with differential weighting of groups of variables. When each analysis variable defines a group the latter method becomes a variable weighting method. For objects the weights are assumed to be given; for groups of variables they may be given, or estimated. These weighting schemes can also be combined and have several important applications. For example, they make it possible to perform efficient analyses of large data sets, to use the distance-based variety of nonlinear multivariate data analysis as an addition to loglinear analysis of multiway contingency tables, and to do stability studies of the solutions by applying the bootstrap on the objects or the variables in the analysis. These and other applications are discussed, and an efficient algorithm is proposed to minimize the corresponding loss function.This study is funded by The Netherlands Organization for Scientific Research (NWO) by grant nr. 030-56403 for the PIONEER project Subject Oriented Multivariate Analysis to the third author.     

Measurement invariance of personality traits from a five-factor model perspective: multi-group confirmatory factor analyses of the HP5 inventory

Associations between personality and health may be influenced by contextual factors varying across studied cohorts. Moreover, measurement bias related to contextual factors could also influence these associations. Gender and age have been discussed as important contextual factors when studying personality and health outcomes. An examination of measurement invariance across gender and age may therefore be warranted. In the present study, measurement invariance across age and gender was examined for a five-factor model of personality traits in which scales have been included to operationalise lower-order traits related to health-behaviour or health outcomes. Using multi-group confirmatory factor analysis on a population based cohort (n= 5700), all important parameters of the measurement model were found to be invariant. On the basis of this invariant model, hypotheses of mean differences across age and gender in personality traits were tested. These results were discussed in relation to meta-analyses on personality change and gender differences in personality.     

Reliability and validity evidence for the French Psychological Need Thwarting Scale (PNTS) scores: Significance of a distinction between thwarting and satisfaction of basic psychological needs

ObjectivesThe goal of these studies was to provide evidence of the significance of a distinction between basic psychological need thwarting (BPNT) and satisfaction (BPNS) within a sport context. Studies 1a and 2 tested the score validity and reliability of the French PNTS (Psychological Need Thwarting Scale) for measuring BPNT for autonomy, competence, and relatedness. Study 1b examined the relationships between BPNT and selected variables (athlete burnout and sport motivation) by controlling for BPNS.MethodParticipants in study 1 (N study 1a = 239; N study 1b = 132) and study 2 (N = 132) were adolescents athletes who completed the PNTS and other questionnaires. Data were analyzed with internal consistency, average variance extracted, composite reliability, confirmatory factor analyses (studies 1a and 2) and correlational analyses (studies 2 and 1b).DesignCross-sectional.ResultsResults of studies 1a and 2 showed that the 11-item 3-factor correlated structure of the PNTS fitted the data adequately. Multiple-group CFAs showed that the PNTS scores were partially invariant across the samples from studies 1a and 2. In study 2, BPNS positively correlated with self-determined forms of motivation and negatively correlated with controlled forms of motivation and/or athlete burnout whereas BPNT showed the opposite pattern of results. In study 1b, BPNT was associated with athlete burnout and sport motivation after BPNS was held constant.ConclusionsThis study provided support for the reliability and validity of the French PNTS scores (studies 1a and 2) and the incremental validity of BPNT (study 1b), supporting the distinction between BPNS and BPNT.     

A bayesian estimation of factor score in confirmatory factor model with polytomous, censored or truncated data

The posterior analysis in estimating factor score in a confirmatory factor analysis model with polytomous, censored or truncated data is investigated in this paper. For the above three types of data, posterior distributions of the factor score are studied, and the estimators of the factor score are obtained to be the location parameters of the posterior distributions. The accuracy of Bayesian estimates is studied via simulation studies.This research was supported by a Hong Kong UGC grant.     

Beyond principal component analysis: A trilinear decomposition model and least squares estimation

The paper derives sufficient conditions for the consistency and asymptotic normality of the least squares estimator of a trilinear decomposition model for multiway data analysis.     

The big none: No evidence for a general factor of personality in chimpanzees, orangutans, or rhesus macaques

We examined whether a general factor of personality (GFP) was present in chimpanzees, orangutans, or rhesus macaques. We used confirmatory factor analysis (CFA) to model correlations among first-order factors as arising from a GFP. We then conducted principal axis factor analyses (PFA) of the first-order factors to extract a single higher-order factor and then to extract two oblique higher-order factors. The CFA model fit was poor for chimpanzees and orangutans, but not rhesus macaques. The single higher-order factors extracted via PFA did not resemble the GFP in all three species. The oblique higher-order factors extracted via PFA were only weakly correlated in all three species. These results do not support the existence of a GFP in nonhuman primates.