Thurstonian Scaling of Compositional Questionnaire Data

To prevent response biases, personality questionnaires may use comparative response formats. These include forced choice, where respondents choose among a number of items, and quantitative comparisons, where respondents indicate the extent to which items are preferred to each other. The present article extends Thurstonian modeling of binary choice data (Brown & Maydeu-Olivares, 2011a) to “proportion-of-total” (compositional) formats. Following Aitchison (1982), compositional item data are transformed into log-ratios, conceptualized as differences of latent item utilities. The mean and covariance structure of the log-ratios is modelled using Confirmatory Factor Analysis (CFA), where the item utilities are first-order factors, and personal attributes measured by a questionnaire are second-order factors. A simulation study with two sample sizes, N=300 and N=1000, shows that the method provides very good recovery of true parameters and near-nominal rejection rates. The approach is illustrated with empirical data from N=317 students, comparing model parameters obtained with compositional and Likert scale versions of a Big Five measure. The results show that the proposed model successfully captures the latent structures and person scores on the measured traits

Estimation and optimal designing under latent variable models for paired comparisons studies via a multiplicative algorithm

We consider:<BR/> 1. The problem of estimating the parameters of latent variable models such as the Bradley Terry or Thurstone Model by the method of maximum likelihood, given data from a paired comparisons experiment. The parameters of these models can be taken to be weights which are positive and sum to one;<BR/> 2. The problem of determining approximate locally optimal designs for good estimation of these parameters; i.e of determining optimal design weights which are also positive and sum to one

Personality Assessment, Forced-Choice.

Instead of responding to questionnaire items one at a time, respondents may be forced to make a choice between two or more items measuring the same or different traits. The forced-choice format eliminates uniform response biases, although the research on its effectiveness in reducing the effects of impression management is inconclusive. Until recently, forced-choice questionnaires were scaled in relation to person means (ipsative data), providing information for intra-individual assessments only. Item response modeling enabled proper scaling of forced-choice data, so that inter-individual comparisons may be made. New forced-choice applications in personality assessment and directions for future research are discussed

Estimation of individual genetic and environmental factor scores

Implicit in the application of the common‐factor model as a method for decomposing trait covariance into a genetic and environmental part is the use of factor scores. In multivariate analyses, it is possible to estimate these factor scores for the communal part of the model. Estimation of scores on latent factors in terms of individual observations within the context of a twin/family study amounts to estimation of individual genetic and environmental scores. Such estimates may be of both theoretical and practical interest and may be provided with confidence intervals around the individual estimates. The method is first illustrated with simulated twin data and next is applied to blood pressure data obtained in a Dutch sample of 59 male adolescent twin pairs. Subjects with high blood pressure can be distinguished into groups with high genetic or high environmental scores. Copyright © 1990 Wiley‐Liss, Inc., A Wiley Compan

Timesharing in relation to broad ability domains

[Abstract]: The concept of a timesharing ability has been the subject of considerable interest in recent times. The present study set out to determine whether a timesharing factor can be identi¬fied when a number of competing tasks are presented in the midst of a range of single tests designed to sample a broad range of psychological dimensions. Evidence for the existence of such a factor would form an important addition to our knowledge of human cognitive functioning. The framework for the study was provided by the theory of fluid and crystallized intelligence. A battery of single and competing tasks was presented to 126 subjects. The competing tasks represented a variety of within- and across-factor combinations from different levels of the (Gf/Gc) hierarchy. Modality of presentation was also varied in some combinations. On the basis of evidence presented in this study, it would be pre¬mature to seek to include a timesharing factor in the (Gf/Gc) model of intelligence

Using rank data to estimate health state utility models

In this paper we report the estimation of conditional logistic regression models for the Health Utilities Index Mark 2 and the SF-6D, using ordinal preference data. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using ordinal data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that ordinal data have the potential to provide useful insights into community health state preferences. However, important questions remain