Additive structure in qualitative data: An alternating least squares method with optimal scaling features

A method is developed to investigate the additive structure of data that (a) may be measured at the nominal, ordinal or cardinal levels, (b) may be obtained from either a discrete or continuous source, (c) may have known degrees of imprecision, or (d) may be obtained in unbalanced designs. The method also permits experimental variables to be measured at the ordinal level. It is shown that the method is convergent, and includes several previously proposed methods as special cases. Both Monte Carlo and empirical evaluations indicate that the method is robust.This research was supported in part by grant MH-10006 from the National Institute of Mental Health to the Psychometric Laboratory of the University of North Carolina. We wish to thank Thomas S. Wallsten for comments on an earlier draft of this paper. Copies of the paper and of ADDALS, a program to perform the analyses discussed herein, may be obtained from the second author.     

An individual differences additive model: An alterating least squares method with optimal scaling features

An individual differences additive model is discussed which represents individual differences in additivity by differential weighting of additive factors. A procedure for estimating the model parameters for various data measurement characteristics is developed. The procedure is evaluated using both Monte Carlo and real data. The method is found to be very useful in describing certain types of developmental change in cognitive structure, as well as being numerically robust and efficient.The work reported here was partly supported by Grant A6394 to the first author by the Natural Sciences and Engineering Research Council of Canada.     

The impact of posttraumatic growth,transformational leadership,and self-efficacy on PTSD and depression symptom severity among combat Veterans

Previous research has established self-efficacy as essential to postdeployment adjustment among Veterans, and perceived transformational leadership is well known for its positive effects on follower outcomes across contexts. However, little is known regarding how transformational leadership may relate to posttraumatic growth and self-efficacy in fostering psychological wellbeing among combat Veterans. The purpose of this study was to examine the role of transformational leadership in predicting posttraumatic stress disorder (PTSD) and depression symptoms among combat Veterans, as well as how posttraumatic growth and postdeployment coping self-efficacy may influence these relations. The study sample consisted of 130 combat Veterans recruited from a university, Veterans Affairs medical center, and the greater community. Path analysis based on bootstrapped resampling revealed postdeployment coping self-efficacy and perceived transformational leadership as predictors of lower PTSD and depression symptom severity. In addition, mediation modeling revealed that postdeployment coping self-efficacy mediated the relation between transformational leadership and both PTSD and depression, while posttraumatic growth did not predict PTSD symptoms. These findings may aid in the prediction of PTSD and depression symptoms among Veterans, which may then influence pre-deployment leadership training among military personnel as well as clinical treatment protocols for Veterans.     

Asian American college women's body image: a pilot study

The purpose of this study was to examine the effects of values acculturation and the influence of media on Asian American college women's overall body image. A sample of 59 Asian American women from two large universities completed self-report surveys, which included questions regarding values acculturation, media internalization, and overall body satisfaction. Results showed that Asian American women who identified more strongly with traditional Asian values reported higher levels of body image dissatisfaction. Further, Asian American women who reported higher internalization of media portrayals of beauty ideals reported higher body image dissatisfaction. Research and clinical recommendations are made to enhance psychologists' understanding of Asian American women's body image and acculturation.     

Consistent curricular choice and congruence of subsequent changes

Curriculum choices of 324 male and 157 female liberal arts students who took the Strong-Campbell Interest Inventory (SCII) during freshman orientation were classified as congruent or incongruent on the basis of rated correspondence between three-letter codes derived from (SCII) Holland theme scales and expressed curricular choice. The choices of those subjects reporting one or more changes in five semesters were examined for level of congruence using a two-way analysis of variance with repeated measures. While serious methodological limitations are noted, analysis of variance procedures indicated that congruent subjects tended to be more stable, more differentiated, and more academically oriented than incongruent subjects. Among subjects who reported one or more changes, Artistic subjects decreased in congruence while Investigative subjects showed no overall change. Results are discussed in terms of recent theory and previous research.     

Multidimensional scaling of nominal data: The recovery of metric information with alscal

Multidimensional scaling has recently been enhanced so that data defined at only the nominal level of measurement can be analyzed. The efficacy of ALSCAL, an individual differences multidimensional scaling program which can analyze data defined at the nominal, ordinal, interval and ratio levels of measurement, is the subject of this paper. A Monte Carlo study is presented which indicates that (a) if we know the correct level of measurement then ALSCAL can be used to recover the metric information presumed to underlie the data; and that (b) if we do not know the correct level of measurement then ALSCAL can be used to determine the correct level and to recover the underlying metric structure. This study also indicates, however, that with nominal data ALSCAL is quite likely to obtain solutions which are not globally optimal, and that in these cases the recovery of metric structure is quite poor. A second study is presented which isolates the potential cause of these problems and forms the basis for a suggested modification of the ALSCAL algorithm which should reduce the frequency of locally optimal solutions.