Resistance revisited

It was a coincidence that I was asked to talk about resistance at Ground Rounds at the University of Texas, Department of Psychiatry, on the tenth anniversary of mailing the first version of Death of Resistance to a journal in 1979. Although the paper was subsequently rejected 17 times and revised six times, it was eventually published inFamily Process (de Shazer, 1984). I still insist that the concept of resistance was a bad idea for therapists to have in their heads.This paper was presented April 14, 1989, at Ground Rounds, University of Texas, Southwest Medical Center, Department of Psychiatry, Dallas, Texas.     

Factor structure in groups selected on observed scores

A new method is proposed for estimating factor means and factor covariances in a group of individuals selected on their observed scores. The selection variable is, for example, the total score on an admissions test. Given a factor model for the test items based on the group of test takers, we may be interested in the factor structure for those in the top quartile. The differences in factor means and covariances between this selected group and the full group gives useful information both on successful test performance and on test validity. The new method draws on the classic Pearson-Lawley selection formulas. It avoids the fallacy of factor analysis on the selected group, which would lead to incorrect estimates. The new method is applied to a simple factor structure model for the GMAT test. Although the majority of the GMAT items test verbal skills, it is found that a quantitative factor shows the greatest change in moving from average to top quartile test takers.     

Correspondence analysis used complementary to loglinear analysis

Loglinear analysis and correspondence analysis provide us with two different methods for the decomposition of contingency tables. In this paper we will show that there are cases in which these two techniques can be used complementary to each other. More specifically, we will show that often correspondence analysis can be viewed as providing a decomposition of the difference between two matrices, each following a specific loglinear model. Therefore, in these cases the correspondence analysis solution can be interpreted in terms of the difference between these loglinear models. A generalization of correspondence analysis, recently proposed by Escofier, will also be discussed. With this decomposition, which includes classical correspondence analysis as a special case, it is possible to use correspondence analysis complementary to loglinear analysis in more instances than those described for classical correspondence analysis. In this context correspondence analysis is used for the decomposition of the residuals of specific restricted loglinear models.     

Early adolescent egocentrism: a review of six articles

This paper reviews six articles which appear to be representative of the past fifteen years during which researchers have focused on early adolescent egocentrism. Each article is described in chronological order and compared to research findings suggested by the other articles. Although the researchers have suggested some interesting associations, there is a lack of consistency among their findings. The author indicates methodological problems and questions for further research which arise from the reviewed articles.     

Lay conceptions of personality: Eliciting tiers of a scientific conception of personality

Two studies are reported which examine the availability of scientific propositions of personality in lay conceptions of personality. It is argued from a social constructivist perspective that models of personality must derive from and refer to lay conceptions of persons. Eysenck's trait-type model of introversion-extraversion, containing specific propositions about phenotypic and genotypic differences between extraverts and introverts, was utilized as the scientific model of personality and its availability in lay conceptions of personality was examined in two studies. In the first study, subjects were presented with a genotypic characterization of either an introvert or an extravert target person and asked to infer corresponding phenotypic differences. In the second study, the inference process was reversed with subjects being asked to infer genotypic characteristics of introverts versus extraverts on the basis of phenotypic target person desecrations of the two types. Results from both studies show a high degree of accuracy in subjects' inferences, suggesting that laypersons have well-formed conceptions about personality containing ‘higher-order’ psychogenetic propositions corresponding to Eysenck's trait-type model. The implications of the findings for theory construction are discussed.     

Sexual experience and preference for males or females in the female rat

The influence of sexual experience on preference behavior was investigated in adult female rats. In the first experiment, preference behavior for sexually active males versus estrous females was investigated in female rats who were experienced with mounting behavior. Preference of these mount experienced females was compared to preference of females who were naive in this respect. Mount experience with estrous females induced a female-directed preference in ovariectomized female rats, irrespective of whether the females were treated with OIL or with testosterone-propionate (500 micrograms TP, injected once 48 h prior to testing). Sexually naive, OIL-treated females did not show a preference for males or females, but TP induced a preference for a male. Individual differences in mount frequency were not correlated with preference behavior. In the second experiment, the influence of experience with feminine sexual responses on preference behavior was investigated. OIL-treated and TP-treated females oriented equally toward males and females when they had been given the opportunity to copulate with males prior to the preference tests. The results strongly suggest that prior sexual experience is an important determinant of preference behavior. The female's behavior during sexual interactions was, however, not predictive of later preference.     

Social structure features in three inbred strains of mice, C57Bl/6J, Balb/cj, and NIH: a comparative study

Some features of social living were investigated in three inbred strains of mice: C57Bl/6j, Balb/cj, and NIH. Five social behaviors--Aggression, Submission, Allogrooming, Social Rest and Rest Alone, as well as Wheel Running Activity--were recorded 2 h daily for a week, in 26 groups of seven male mice living in an enriched environment. Dominants and subordinates among strains shared some behavioral characteristics, but strain contributions upon social structure were also detected. Similarities among strains included the appearance of a single dominant mouse per group rated as the most aggressive, besides from being the animal presented with most Submissions. Allogrooming was more frequent among subordinates than among dominants and subordinates. Differences among strains were that agonistic behavior among subordinates was higher in the Balb/cj and NIH groups than in the C57Bl/6j mice. NIH mice were recorded in Rest Alone more often than mice from the other strains. C57Bl/6j dominants showed higher rates of Wheel Running Activity than subordinates.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.