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.     

The representation of nonuniform motion: induced movement

Induced motion occurs when there is a misallocation of nonuniform motion. Theories of induced motion are reviewed with respect to the model for uniform motion recently proposed by Swanston, Wade, and Day. Theories based on single processes operating at one of the retinocentric, orbitocentric, egocentric, or geocentric levels are not able to account for all aspects of the phenomenon. It is therefore suggested that induced motion is a consequence of combining two different types of motion signals: one provides information by registering the motion with respect to the retina, orbit, and egocentre; the other provides information only on the relational motions between the pattern elements. Simple rules are given for defining a frame of reference for the relational motion process, which can result in a reallocation of the motion signals. It is proposed that the two signals in combination are weighted differentially, with the greater influence coming from the relational signals. Procedures for determining the weighting factors are described, and predictions from the model are examined.     

The development of sex differences in young children's activities at home: The effect of the social context

Randomly scheduled spot observations of 83 zero to six-year-old American middle-class children were used to investigate factors affecting the development of sex differences in young children's activities in and near their home. Sex and age differences in children's typical play and nonplay activities and in the people with whom they did activities were examined. The results showed that there were fewer sex differences in children's activities, activity partners, and general social settings than expected. Girls spent more time engaged in housework and school-related activities than boys, while boys spent more time in social gross motor play with other children and in self-care activities than girls. Children spent a surprisingly large amount of their time with members of their immediate family — particularly their mother and one other sibling. Boys and girls did not differ, however, in the time they were in settings or doing activities with their father, with their mother, or with same-or mixed-sex child groups.This research was supported by an award to the author from the Wisconsin Alumnae Research Foundation at the University of Wisconsin — Madison. The author would also like to acknowledge the research and editorial assistance of Daniel J. Walsh. In addition, Aletha Huston, Beatrice B. Whiting, and Gary G. Price provided valuable advice on this and earlier versions of this paper.     

It's not who you are but who you're with: Self-Confidence in achievement settings

This study examined the effects of two social cues on women's and men's self-confidence: the sex and performance of another in an achievement setting. Before trying to solve 60 anagrams, women expected to perform more poorly than men. In addition, both sexes expected to perform more poorly when paired with a male confederate than when paired with a female confederate. The effect of the partner's sex showed up in anagram performance: people with a female partner solved more anagrams than people with a male partner. The effect of subject's sex on performance was unexpected: women solved more anagrams than men. After the task, sex differences in self-confidence disappeared; neither sex of subject nor sex of partner influenced self-confidence. The partner's performance, however, had a strong effect on everyone: people were less self-confident if they had worked with a high-scoring partner. The pattern of results suggests that sex-of-subject differences in self-confidence, while important, are less powerful than the effects wielded by the sex of others in achievement settings.