Confidence regions for INDSCAL using the jackknife and bootstrap techniques

Bootstrap and jackknife techniques are used to estimate ellipsoidal confidence regions of group stimulus points derived from INDSCAL. The validity of these estimates is assessed through Monte Carlo analysis. Asymptotic estimates of confidence regions based on a MULTISCALE solution are also evaluated. Our findings suggest that the bootstrap and jackknife techniques may be used to provide statements regarding the accuracy of the relative locations of points in space. Our findings also suggest that MULTISCALE asymptotic estimates of confidence regions based on small samples provide an optimistic view of the actual statistical reliability of the solution. The authors wish to thank Geert DeSoete, Richard A. Harshman, William Heiser, Jon Kettenring, Joseph B. Kruskal, Jacqueline Meulman, James O. Ramsay, John W. Tukey, Paul A. Tukey, and Mike Wish. Sharon L. Weinberg is a consultant at AT&T Bell Laboratories, Murray Hill, New Jersey 07974.     

A visual approach to statistical power analysis on the microcomputer

Computer programs for statistical power analysis typically require the user to provide a series of values and respond by reporting the corresponding power. These programs provide essentially the same functions as a published text, albeit in a more convenient form. In this paper, we describe a program that instead uses innovative graphic techniques to provide insight into the interaction among the factors that determine power. For example, fort tests, the means and standard deviations of the two distributions, sample sizes, and alpha are displayed as bar graphs. As the researcher modifies these values, the corresponding values of beta (also displayed as a bar graph) and power are updated and displayed immediately. By displaying all of the factors that are instrumental in determining power, the program ensures that each will be addressed By allowing the user to determine the impact that any modifications will have on power, the program encourages an appropriate balance between alpha and beta while working within the constraints imposed by a limited sample size. The program also allows the user to generate tables and graphs to document the impact of the various factors on power. In addition, the program enables the user to run on-screen Monte Carlo simulations to demonstrate the importance of adequate statistical power, and as such, it can serve as a unique educational tool.     

Psychoanalytic training today.

Psychoanalytic education in the United States faces multiple challenges as we enter the last decade of this century. (1) Changing interest and career path patterns for psychiatrists have resulted in fewer medical applications for psychoanalytic training. (2) Increased opportunities for full psychoanalytic training of nonphysicians have resulted in increased applications from highly skilled clinicians who often have more clinical experience than their medical colleagues. (3) Increased enrollment of women candidates has required rethinking of progression requirements, in light of their combined careers as professionals and mothers. (4) Independent institutes not accredited by the American Psychoanalytic Association compete for applicants while maintaining training standards that require less time and immersion in psychoanalytic theory and practice. (5) Economic factors increasingly influence the desirability of prolonged psychoanalytic training and the availability of suitable analysands for control analyses. (6) Evolution of theory and practice and the emergence of "new schools" of psychoanalytic thought have rendered the previous psychoanalytic landscape dominated by drive theory and ego psychology more multifaceted and less uniform. The American Psychoanalytic Association and its institutes attempt to understand these changing patterns and take them into consideration in the design and implementation of psychoanalytic training programs. Only one aspect of this complex situation will be described in this work, the current state of psychoanalytic training in the 28 institutes accredited by the American Psychoanalytic Association. Although the data available at this time leave unanswered many important questions about the philosophies that organize the content and emphases of the curriculum in different institutes, much has been learned about the overall structure of psychoanalytic training programs.     

Combining discrepant diagnostic information from multiple sources: Are complex algorithms better than simple ones?

Optimizing methods of combining discrepant diagnostic information from multiple sources is one of the more daunting tasks facing the field of child psychopathology. Several researchers have asserted that complex information-combining schemes, those in which certain information or sources of information are weighted differently from others, are preferable. This study provides theoretical and empirical evidence that simple information-combining schemes, those in which all information from all sources is weighted equally, will as a rule work as well as complex schemes and may even work better. The implications of these findings for diagnostic instrument and algorithm design are discussed. A two-step diagnostic procedure utilizing a simple information-combining scheme is presented.     

The effect of constant outcome value on judgments and decision making given linguistic probabilities

Two experiments were performed to determine whether judgments of the relative chances of two independent events occurring are biased by constant outcome values contingent on the events when the uncertainties are specified by linguistic expressions (e.g. doubtful). In Experiment 1, subjects directly judged the relative chances of the two events, of which one was represented by a spinner and the other by a linguistic probability expression. In Experiment 2, only linguistic probability expressions were used to describe the two events and a betting procedure was used. A bias was evident in both studies, such that the relative judgments tended to favour the event with the positive rather than the negative contingent outcome. The bias was smaller for the low- than for the high-probability phrases. Individual differences were great, with the bias appearing strongly in only about one-third of the population. Theoretical implications of the present and related results are discussed.     

CHRONIC SOCIAL STRESS, AFFILIATION, AND CELLULAR IMMUNE RESPONSE IN NONHUMAN PRIMATES

Abstract ——We report the first experimental study of the effect of long–term (over 2 years) exposure to a stressor on cellular immune response Forty–three male cynomolgus monkeys were randomly assigned to stable or unstable social conditions for 26 months The proportion of time spent in affiliative behaviors was assessed by observations made twice weekly T–cell immune response (mitogen–stimulated cell proliferation) was assessed weekly for 3 weeks immediately following the 26–month manipulation The possibility that affiliative behavior represents an attempt to cope with social stress was supported by greater affiliation among animals m the unstable condition than in the stable condition Animals in the unstable condition also demonstrated relatively suppressed immune response More affiliative animals showed enhanced immune response, with the beneficial effects of affiliation occurring primarily among unstable animals The data are interpreted as consistent with the stress–buffering hypothesis, that IS, affiliation protects animals from the potentially pathogenic influences of chronic social stress     

Lay Explanations of Wealth: Attributions for Economic Success1

The explanations people give for wealth, or financial success, are not only of considerable political importance, but also offer an opportunity to assess some of the implications of attribution theory in a real-lie setting. In the present study, 324 subjects from all walks of life and a variety of socioeconomic and demographic backgrounds were asked to anonymously complete an extensive questionnaire assessing their (a) free response explanations of the most common sources of wealth, (b) estimates of necessary income levels for “wealth” and “a decent life,” and (c) attribution judgments for likely causes of wealth in five target categories of people. The target categories were manipulated in terms of social class and ethnicity, to include native born and migrant, and middle- and working-class characters, as well as attributions to an unspecified other. Results showed that judges used four major attributional categories in explaining wealth (external-social, internal/individual, family background, and luck-risk factors), and that both the target persons' class and ethnicity significantly influenced the attribution strategies used. In addition, the judges' socioeconomic background, demographic position, and voting preferences also significantly affected preferred attributions and estimates of income levels. These results are discussed in terms of the role of social, political, and ideological factors in everyday explanations, and their implications for some assumptions of attribution research are considered.