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.     

On rotating to smooth functions

Tucker has outlined an application of principal components analysis to a set of learning curves, for the purpose of identifying meaningful dimensions of individual differences in learning tasks. Since the principal components are defined in terms of a statistical criterion (maximum variance accounted for) rather than a substantive one, it is typically desirable to rotate the components to a more interpretable orientation. Simple structure is not a particularly appealing consideration for such a rotation; it is more reasonable to believe that any meaningful factor should form a (locally) smooth curve when the component loadings are plotted against trial number. Accordingly, this paper develops a procedure for transforming an arbitrary set of component reference curves to a new set which are mutually orthogonal and, subject to orthogonality, are as smooth as possible in a well defined (least squares) sense. Potential applications to learning data, electrophysiological responses, and growth data are indicated.Portions of this research were supported by the National Research Council of Canada, Grant A8615 to the second author. We thank Jagdeth Sheth for supplying his raw data.     

Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A monte carlo study

In order to make the parallel analysis criterion for determining the number of factors easy to use, regression equations for predicting the logarithms of the latent roots of random correlation matrices, with squared multiple correlations on the diagonal, are presented. The correlation matrices were derived from distributions of normally distributed random numbers. The independent variables are log (N–1) and log {[n(n–1)/2]–[(i–1)n]}, whereN is the number of observations;n, the number of variables; andi, the ordinal position of the eigenvalue. The results were excellent, with multiple correlation coefficients ranging from .9948 to .9992.This research was supported by the Office of Naval Research under Contract N00014-67-A-0305-0012, Lloyd G. Humphreys, principal investigator, and by the Department of Computer Science of which Richard G. Montanelli, Jr., is a member.     

Comments on “the measurement of factorial indeterminacy”

Guttman's index of indeterminacy (2² – 1) measures the potential amount of uncertainty in picking the right alternative interpretation for a factor. When alternative solutions for a factor are equally likely to be correct, then the squared multiple correlation ² for predicting the factor from the observed variables is the average correlation _AB between independently selected alternative solutionsA andB, while var ( _AB )=(1 – ²)²/s, wheres is the dimensionality of the space in which unpredicted components of alternative solutions are to be found. When alternative solutions for the factor are not equally likely to be chosen, ² is the lower bound for E( _AB ); however, E( _AB ) need not be a modal value in the distribution of _AB . Guttman's index and E( _AB ) measure different aspects of the same indeterminacy problem.     

A look,by simulation,at the validity of some asymptotic distribution results for rotated loadings

In the last few years, a number of asymptotic results for the distribution of unrotated and rotated factor loadings have been given. This paper investigates the validity of some of these results based on simulation techniques. In particular, it looks at principal component extraction and quartimax rotation on a problem with 13 variables. The indication is that the asymptotic results are quite good.     

Infants’ behavioral styles in joint attention situations and parents’ socio-economic status

In this study the eco-cultural model of parenting (Keller, H. (2007). Cultures of infancy. Mahwah, NJ: Erlbaum) was applied to the study of joint attention behavior of children from families with different socio-economic status (SES). It was hypothesized that infants’ early communication styles would differ with SES reflecting more independent or interdependent interactions with their caregivers. It was also hypothesized that infants would use the same types of behaviors whether they have declarative or imperative communication goals. The Early Social Communication Scales (ESCS, Mundy et al., 2003) was administered to 103 typically developing infants of 12 months (approximately half of them siblings of children with autism). A factor analysis, yielding four behavioral factors, namely pointing, eye contact, actions and following points, confirmed the hypothesis that infants use behaviors consistently across situations independent of their communicative intent. MANOVAs (comprising parental education and income) revealed that higher SES infants showed actions more frequently in the ESCS whereas lower SES infants followed experimenter's points more frequently. The results are discussed in the context of presumably differing socialization goals for infants and the divergent contribution of parental education and income that seem to have additive contribution to some factors (actions, following points) but divergent contributions to others (pointing, eye contact).     

Changing the Criminal Justice System Response to Sexual Assault: An Empirical Study of a Participatory Action Research Project

In jurisdictions throughout the United States, thousands of sexual assault kits (SAKs; also known as a “rape kits”) have not been submitted by the police for forensic DNA testing. DNA evidence may be helpful to sexual assault investigations and prosecutions by identifying perpetrators, revealing serial offenders through DNA matches across cases, and exonerating those who have been wrongly accused. This paper describes a longitudinal action research project conducted in Detroit, Michigan after that city discovered approximately 11,000 untested sexual assault kits in a police department storage facility. We conducted a root cause analysis to examine individual, organizational, community, and societal factors that contributed to the development of the rape kit backlog in Detroit. Based on those findings, we implemented and evaluated structural changes to increase staffing, promote kit testing, and retrain police and prosecutors so that cases could be reopened for investigation and prosecution. As we conducted this work, we also studied how this action research project impacted the Detroit criminal justice system. Participating in this project changed stakeholders’ attitudes about the utility of research to address community problems, the usefulness of DNA evidence in sexual assault cases, and the impact of trauma on survivors. The results led to new protocols for SAK testing and police investigations, and new state legislation mandating SAK forensic DNA testing.     

Enhancing the care of children with chronic diseases through the narratives of patient,physician, nurse and carer

We tested the hypothesis that a narrative approach may enhance a bio‐psycho‐social model (BPS) in caring for chronically ill children. Forty‐eight narratives were collected from 12 children with six different medical conditions, their mothers, physicians, and nurses. By a textual analysis, narratives were classified on their predominant focus as disease (biological focus), illness (psychologic focus), or sickness (social focus). Sixty‐one percent of narrative’ text were classified as illness, 28% as disease and 11% as sickness. All narratives had a degree of illness focus. Narratives by patients and physicians on the one hand, and nurses’ and mothers’ on the other were disease focused. Narratives were also evaluated with respect to the type of medical condition: Illness was largely prevalent in all but Crohn’s disease and HIV infection, the latter having a predominance of sickness most probably related to stigma. Narrative exploration proved a valuable tool for understanding and addressing the needs of children with complex conditions. Narrative approaches allow identification of the major needs of different patients according to health conditions and story tellers. In the narratives, we found a greater illness and disease focus and surprisingly a low sickness focus, except with HIV stories. Narrative medicine provides a tool to strengthen the BPS model in health care.     

Caveats of non-ipsatization of basic values: A review of issues and a simulation study

Ipsatization, or a correction of variables by their common component, is routinely applied to measures of basic values. Although ipsatization has been criticized, the consequences of non-ipsatization are rarely discussed. We show that the ipsatization of values is intertwined with their definition. A common factor involved in ipsatization was suggested to represent a nuisance variable, a response style, social desirability, or other constructs. A simulation study illustrated that within-individual centering revealed more accurate value scores when the common factor was in the data, with exception of the situation when values were consistently and positively correlated with each other. We conclude that in different conditions both applying and failing to apply ipsatization can cause bias. Therefore, no general advice in regard to ipsatization can be provided.