A multivariate model for discrimination methods

We describe a multivariate model for a certain class of discrimination methods in this paper and discuss a multivariate Euclidean model for a particular method, the triangular method. The methods of interest involve the selection or grouping of stimuli drawn from two stimulus sets on the basis of attributes invoked by the subject. These methods are commonly used for estimation and hypothesis testing concerning possible differences between foods, beverages, odorants, tastants and visual stimuli.Mathematical formulation of the bivariate model for the triangular method is provided as well as extensive Monte Carlo results for up to 10-dimensional cases. The effect of correlation structure and variance inequality are discussed. Results from these methods (as probability of a correct response) are not monotonically related to the distance between the means of the stimulus sets from which the stimuli are drawn but depend in a particular way on dimensionality, correlation structure, and the relative orientation of the momentary sensory values in a multidimensional space. The importance of these results to the validity of these methods as currently employed is discussed and the possibility of developing a new approach to multidimensional scaling on the basis of this new theory is considered.     

His and her marriage: A multivariate study of gender and marital satisfaction

This study examined gender differences in marital satisfaction using the multidimensional marital inventory ENRICH. Contrary to previous research, the results indicated that men are somewhat more satisfied with their marriages than women. The findings also suggest that religion is a more important part of the marriage for men, whereas women esposed egalitarian roles to a greater extent. A significant interaction was found between marital distress and gender on the Sexual Relationship, Communication, Parenting and Children, and Equalitarian Roles scales, indicating that these areas may be particularly important in distressed couples. The differences in husbands' and wives' marital satisfaction found in this study are consistent with research suggesting that men obtain greater mental health benefits from marriage than do women. The explanation of the obtained gender differences are discussed with regard to measurement issues, sampling procedures, and power and task inequities. Sampling and differences in marital tasks and power are cited as the best explanations of the findings.     

A model of resilience and marital satisfaction

This article examined the hypothesis that resilience mediates the relationship between marital satisfaction and a host of relevant variables, including spousal attachment, social support, and affect. Participants were 195 married individuals, who completed online surveys about their marriage. Importantly, the findings indicated that resilience has a direct effect on marital satisfaction. In addition, affect and social support were each shown to indirectly impact satisfaction through resilience. The relationships between spousal attachment, resilience, and satisfaction were more complicated than predicted and are further discussed. Overall, the results demonstrate the importance of resilience in marital satisfaction.     

A comprehensive model and measure of compensation satisfaction

We describe the results of two studies designed to develop a comprehensive theoretical model and measure of compensation satisfaction. Our typology of compensation satisfaction consists of seven dimensions: four for pay (level, structure, raises, and variable pay procedures satisfaction) and three dimensions for benefits (level, determination, and administration satisfaction). We used new and existing items to develop the Comprehensive Compensation Satisfaction Questionnaire. In Study 1, we report the results of exploratory factor analysis that supports a seven‐factor structure. In Study 2, confirmatory factor analysis supported the same seven‐factor structure in a different sample. We examined relationships between the compensation satisfaction dimensions and their antecedents and consequences. Seven hypotheses regarding differential antecedents of compensation satisfaction were supported. Satisfaction with aspects of compensation procedures were related to perceived organizational support, and perceived organizational support mediated the relationships between these compensation satisfaction procedures and affective commitment and turnover intentions. Our final analysis yielded a 29‐item scale (including eight new items) which we recommend for use in future compensation satisfaction research.     

A model of users' satisfaction with Taiwan's Government website

Taiwan's Government web portal has been the sole communication link between citizens and E-Government since being launched in 2002 to provide citizens with government-related information promptly via effective classification. The assessment of the service quality and citizens' satisfaction with E-Government has rarely been explored. The present study explored how the service quality of E-Government subsequently affects the users' psychological and behavioral responses. A structural model was proposed that contained four constructs: service quality, service value, users' satisfaction, and behavioral intention as well as their interrelations. A survey was used to collect users' ratings. Structural equation modeling was applied to verify the factor analysis of the obtained data and fit of a model. Analyses indicated adequate fit of model as follows: E-Government service quality --> service value --> users' satisfaction --> behavioral intention.     

A multivariate reduced-rank growth curve model with unbalanced data

A multivariate reduced-rank growth curve model is proposed that extends the univariate reducedrank growth curve model to the multivariate case, in which several response variables are measured over multiple time points. The proposed model allows us to investigate the relationships among a number of response variables in a more parsimonious way than the traditional growth curve model. In addition, the method is more flexible than the traditional growth curve model. For example, response variables do not have to be measured at the same time points, nor the same number of time points. It is also possible to apply various kinds of basis function matrices with different ranks across response variables. It is not necessary to specify an entire set of basis functions in advance. Examples are given for illustration.The work reported in this paper was supported by Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the second author. We thank Jennifer Stephan for her helpful comments on an earlier version of this paper. We also thank Patrick Curran and Terry Duncan for kindly letting us use the NLSY and substance use data, respectively. The substance use data were provided by Grant DA09548 from the National Institute on Drug Abuse.     

A simple multivariate probabilistic model for preferential and triadic choices

Multidimensional probabilistic models of behavior following similarity and choice judgements have proven to be useful in representing multidimensional percepts in Euclidean and non-Euclidean spaces. With few exceptions, these models are generally computationally intense because they often require numerical work with multiple integrals. This paper focuses attention on a particularly general triad and preferential choice model previously requiring the numerical evaluation of a 2n-fold integral, wheren is the number of elements in the vectors representing the psychological magnitudes. Transforming this model to an indefinite quadratic form leads to a single integral. The significance of this form to multidimensional scaling and computational efficiency is discussed.The authors would like to thank Jean-Claude Falmagne and Norman Johnson for suggestions and advice concerning quadratic forms.     

A latent variable model for discrete multivariate psychometric waiting times

A version of the discrete proportional hazards model is developed for psychometrical applications. In such applications, a primary covariate that influences failure times is a latent variable representing a psychological construct. The Metropolis-Hastings algorithm is studied as a method for performing marginal likelihood inference on the item parameters. The model is illustrated with a real data example that relates the age at which teenagers first experience various substances to the latent ability to avoid the onset of such behaviors.We thank Michael Newton and Daode Huang for their helpful comments and suggestions.     

A model for judgments of work values and job satisfaction

First, a discussion is presented of some previous research results on the relation of a person's assessment of the importance ("value") of an object and his or her attitude toward that object, in particular on the relation of work values with job satisfaction. Then, a model is formulated and simulated to explain how both types of judgments are generated. In Phase 1, the elements of the mental representation of the respective attitude object are aggregated by two composition rules to an overall satisfaction and an overall importance judgment, respectively. In addition, possible dissonance of high importance and low satisfaction is reduced by a coping function.     

A dynamic factor model for the analysis of multivariate time series

As a method to ascertain the structure of intra-individual variation,P-technique has met difficulties in the handling of a lagged covariance structure. A new statistical technique, coined dynamic factor analysis, is proposed, which accounts for the entire lagged covariance function of an arbitrary second order stationary time series. Moreover, dynamic factor analysis is shown to be applicable to a relatively short stretch of observations and therefore is considered worthwhile for psychological research. At several places the argumentation is clarified through the use of examples.I would like to thank WM. van der Molen, G. J. Mellenbergh and L. H. M. Oppenheimer, who provided valuable ideas that led to this formulation.     

Location, location, location: the misprediction of satisfaction in housing lotteries

People tend to overestimate the emotional consequences of future life events, exhibiting an impact bias. The authors replicated the impact bias in a real-life context in which undergraduates were randomly assigned to dormitories (or "houses"). Participants appeared to focus on the wrong factors when imagining their future happiness in the houses. They placed far greater weight on highly variable physical features than on less variable social features in predicting their future happiness in each house, despite accurately recognizing that social features were more important than physical features when asked explicitly about the determinants of happiness. In Experiment 2, we found that this discrepancy emerged in part because participants exhibited an isolation effect, focusing too much on factors that distinguished between houses and not enough on factors that varied only slightly, such as social features.     

A thurstonian pairwise choice model with univariate and multivariate spline transformations

A probabilistic choice model is developed for paired comparisons data about psychophysical stimuli. The model is based on Thurstone's Law of Comparative Judgment Case V and assumes that each stimulus is measured on a small number of physical variables. The utility of a stimulus is related to its values on the physical variables either by means of an additive univariate spline model or by means of multivariate spline model. In the additive univariate spline model, a separate univariate spline transformation is estimated for each physical dimension and the utility of a stimulus is assumed to be an additive combination of these transformed values. In the multivariate spline model, the utility of a stimulus is assumed to be a general multivariate spline function in the physical variables. The use of B splines for estimating the transformation functions is discussed and it is shown how B splines can be generalized to the multivariate case by using as basis functions tensor products of the univariate basis functions. A maximum likelihood estimation procedure for the Thurstone Case V model with spline transformation is described and applied for illustrative purposes to various artificial and real data sets. Finally, the model is extended using a latent class approach to the case where there are unreplicated paired comparisons data from a relatively large number of subjects drawn from a heterogeneous population. An EM algorithm for estimating the parameters in this extended model is outlined and illustrated on some real data.The first author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek. The authors are indebted to Ulf Böckenholt and Yoshio Takane for useful comments on an earlier draft of this paper.     

PLS model building: A multivariate approach to personality test data

The aim of this study was to demonstrate how personality test data can be plotted with a multivariate method known as Partial Least Squares of Latent Structures (PLS). The basic methodology behind PLS modeling is presented and the example demonstrates how a PLS model of personality test data can be used for diagnostic prediction. Principles for validating the models are also presented. The conclusion is that PLS modeling appears to be a powerful method for extracting clinically relevant information from complex personality test data matrixes. It could be used as a complement to more hard modeling methods in the process of examining a new area of interest.     

A prototype matching model of satisfaction in same‐sex friendships

The hypothesis that people experience greater friendship satisfaction when their friendship matches the prototype of intimacy interactions was tested. Consistent with this hypothesis, both women and men reported the greatest satisfaction when their “real‐world” friendship matched the prototype of intimacy interactions. This relation was even stronger when the friendship matched prototypical intimacy interaction patterns (e.g., self‐disclosure) than when it matched nonprototypical patterns (e.g., practical support). Thus, there is evidence that people rely on relational knowledge—in this case, complex knowledge of patterns of relating—when evaluating the quality of their friendships.     

A multivariate model of gender differences in adolescents' internalizing and externalizing problems.

Gender differences observed in interpersonal and self-critical vulnerabilities, reactivity to stressful life events, quality of relationships, and self-concepts inform a multivariate theoretical model of the moderating effects of gender on internalizing and externalizing problems in adolescence. To test this model, data were collected in a 1-year prospective study from an ethnically diverse sample of 460 middle school students. Increases in girls' internalizing symptoms, compared with boys', were partly explained by greater stability in girls' interpersonal vulnerabilities and greater magnitude in coefficients linking girls' relationships with parents and peers and internalizing problems. Boys' risks for externalizing problems, compared with girls', were partly explained by the greater stability in boys' vulnerability to self-criticism. Coefficients for most pathways in the model are similar for boys and girls.     

Determinants of satisfaction with specific job facets: A test of Locke's model

Survey results supported Locke's (1969, 1976) contention that facet job satisfaction is a function of three basic determinants: 1) facet amount; 2) wanted amount; and 3) facet importance. We found several three-way interactions that were generally consistent with Locke's model. Specifically, facet satisfaction was highest when employees wanted a large amount of the facet in question, were currently receiving a large amount, and felt that the facet was personally important. Conversely, satisfaction was lowest when employees wanted a large amount of the facet, were currently receiving only a small amount, and felt that the facet was personally important. When job facets were viewed as unimportant to employees, however, the amount of facet desired and currently possessed had little impact on satisfaction. Implications, limitations, and directions for research are discussed.Bob Rice passed away recently. He will be sorely missed.     

Commitment and satisfaction in romantic associations: A test of the investment model

Two experiments were designed to test the adequacy of the investment model of developing relationships in predicting satisfaction with and commitment to ongoing associations. According to the investment model, attraction to and satisfaction with a relationship is a function of a comparison of the relationship outcome value (both rewards and costs) to the individual's expectations, or comparison level. Commitment to a relationship is said to be a function not only of the relationship outcome value, but also the quality of the best available alternative and the magnitude of the individual's investment in the relationship. The intrinsic or extrinsic investment of resources serves to increase commitment by increasing the costs of leaving the relationship. Thus, increases in investment size, decreases in alternative value, and increases in relationship value should increase commitment to an ongoing relationship. In Experiment 1, a role-playing study, commitment to relationships increased with intrinsic and extrinsic investment size and decreased with the value of alternatives, but was not appreciably affected by relationship costs. Satisfaction/attraction significantly increased as relationship costs decreased. In Experiment 2, a survey of ongoing romantic associations, satisfaction/attraction was predicted by relationship reward value and relationship cost value. Commitment to relationships increased as relationship reward value and investment size increased and as alternative value and relationship cost value decreased, although the effects of cost value were weak.     

Sexual satisfaction in long-term heterosexual relationships: The interpersonal exchange model of sexual satisfaction

This study examined the validity of the Interpersonal Exchange Model of Sexual Satisfaction (IEMSS) in long-term, heterosexual sexual relationships. The IEMSS proposes that sexual satisfaction depends on one's levels of rewards and costs in the sexual relationship, one's comparison levels (CL) for rewards/costs, and one's perceptions of the dyadic equality (EQ) of these rewards/costs. Sexual satisfaction is expected to be greater to the extent that, over time, levels of rewards (REW) exceed levels of costs (CST), relative reward levels (CLREW) exceed relative cost levels (CLcst ), and interpersonal equality of rewards (EQrew ) and of costs (EQCST) is perceived to exist. Married/cohabiting community volunteers and university alumni/staff completed two questionnaires, 3 months apart. The results obtained from this well-educated, relationally satisfied sample (N= 143) provided excellent support for the IEMSS. Hierarchical regression analysis revealed that each component of the model (REW - CST, CLrew - CLcst , and EQrew , EQcst ) added to the prediction of sexual satisfaction as expected, accounting for 75% of the variance. Repeated measurement of the IEMSS components offered a better prediction of sexual satisfaction than a one-time measure alone. Neither gender nor relationship satisfaction interacted with the IEMSS components. However, including relationship satisfaction (but not gender) in the model significantly improved the prediction of sexual satisfaction. It was concluded that the model should be revised to include relationship satisfaction. Both the exchange components of the IEMSS and sexual satisfaction uniquely predicted relationship satisfaction. The IEMSS offers a promising approach for understanding sexual satisfaction and its relationship to relationship satisfaction, as well as for reconciling inconsistent findings in the literature.     

Classical conditioning as a nonstationary,multivariate time series analysis: A spreadsheet model

The implementation of the Gallistel (1990) model of classical conditioning on a spreadsheet with matrix operations is described. The model estimates the Poisson rate of unconditioned stimulus (US) occurrence in the presence of each conditioned stimulus (CS). The computations embody three implicit principles:additivity (of the rates predicted by each CS),provisional stationarity (the rate predicted by a given CS has been constant over all the intervals when that CS was present), andpredictor minimization (when more than one solution is possible, the model minimizes the number of CSs with a nonzero effect on US rate). The Kolmogorov-Smirnov statistic is used to test for non-stationarity. There are no free parameters in the learning model itself and only two parameters in the formally specified decision process, which translates what has been leamed into conditioned responding. The model predicts a wide range of conditioning phenomena, notably: blocking, overshadowing, overprediction, predictive sufficiency, inhibitory conditioning, latent inhibition, the invariance in the rate of conditioning under scalar transformation of CS-US and US-US intervals, and the effects of partial reinforcement on acquisition and extinction.