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.     

DOES EFFORT PLAY A ROLE IN THE EFFECT OF RESPONSE REQUIREMENTS ON DELAYED MATCHING TO SAMPLE?

The possible role of "effort" in the accuracy of pigeons' performance on a delayed matching-to-sample procedure was investigated by examining the effects of response requirements that accompanied a trial-initiating stimulus and that accompanied a sample stimulus. In the first experiment, the effect of varying the size of a fixed-ratio requirement for responses during an initiating stimulus was compared to that of varying a similar requirement for responses during the sample stimulus. Accuracy increased reliably with increases in the ratio scheduled during the sample stimulus, but was not significantly affected by increases in the ratio scheduled on the key during the initiating stimulus. In another phase of Experiment 1, sample duration was held constant while the ratio requirement was varied during the initiating stimulus. Again, accuracy of matching to sample was not significantly affected by the size of the ratio scheduled during the initiating stimulus. Experiment 2 provided a systematic replication of these results in another group of pigeons and included a more detailed analysis of responding. These results support the view that increases in sample-response requirement facilitate accuracy of delayed matching by increasing the durations of exposure to the sample stimuli, and do not support a role of effort in the sample-response effect. In Experiment 3, the facilitative effect of responses on the sample but not of those on the initiating stimulus was replicated using a simultaneous matching-to-sample procedure. This finding provides further evidence against an interpretation of response-requirement effects that appeals to effort; the finding also suggests that sample exposure might affect initial discrimination of the sample rather than remembering the sample.     

A taxonomy of item response models

A number of models for categorical item response data have been proposed in recent years. The models appear to be quite different. However, they may usefully be organized as members of only three distinct classes, within which the models are distinguished only by assumptions and constraints on their parameters. “Difference models” are appropriate for ordered responses, “divide-by-total” models may be used for either ordered or nominal responses, and “left-side added” models are used for multiple-choice responses with guessing. The details of the taxonomy and the models are described in this paper. The present study was supported in part by two postdoctoral fellowships awarded to Lynne Steinberg: an Educational Testing Service Postdoctoral Fellowship at ETS, Princeton, NJ and an NIMH Individual National Research Service Award at Stanford University, Stanford, CA. Helpful comments by the editor and three anonymous reviewers are gratefully acknowledged.     

A note on the computation of the second-order derivatives of the elementary symmetric functions in the rasch model

Jansen (1984) gave explicit formulas for the computation of the second-order derivatives of the elementary symmetric functions. But they are only applicable to those pairs of items which have unequal parameters. It is shown here that for equal parameters similar explicit formulas do exist, too, facilitating the application of the Newton-Raphson procedure to estimate the parameters in the Rasch model and related models according to the conditional maximum likelihood principle.The author wishes to thank the reviewers for their helpful comments on an earlier draft of this paper.     

Estimation for structural equation models with missing data

A direct method in handling incomplete data in general covariance structural models is investigated. Asymptotic statistical properties of the generalized least squares method are developed. It is shown that this approach has very close relationships with the maximum likelihood approach. Iterative procedures for obtaining the generalized least squares estimates, the maximum likelihood estimates, as well as their standard error estimates are derived. Computer programs for the confirmatory factor analysis model are implemented. A longitudinal type data set is used as an example to illustrate the results.This research was supported in part by Research Grant DAD1070 from the U.S. Public Health Service. The author is indebted to anonymous reviewers for some very valuable suggestions. Computer funding is provided by the Computer Services Centre, The Chinese University of Hong Kong.     

When faces and voices come together: Face width-to-height ratio and voice pitch contribute independently to social perception

Prior research has shown that the face's width-to-height ratio (fWHR) and the voice's pitch influence social perception. Yet, the relative contribution of either cue has been largely unexplored. We examined the simultaneous effects of fWHR and pitch on social evaluations. Experiment 1 (N = 102) tested how such cues shaped global impressions. Experiment 2 (N = 121) tested fWHR and pitch's effect on behavioural affiliative intentions, framing social interaction as a physical or an intellectual competition. Experiment 3 (N = 57) assessed whether variations in fWHR and pitch could influence trait attribution (i.e., physical formidability and intelligence). Individuals with large faces or low-pitched voices elicited negative impressions, positive behavioural intentions in a physical competition, and the attribution of stronger formidability but lower intelligence. Across the studies, cues exerted independent effects. The implications of these findings for research on cross-modal social perception are discussed.     

Effects of acute endurance,strength, and coordination exercise interventions on attention in adolescents: A randomized controlled study

ObjectivesThe aim of this study was to compare three different modes of an acute bout of exercise – endurance, strength, and coordination – in their effects on adolescents' attention.DesignThis was a preregistered, prospective, randomized intervention study with four groups and two distinct measurement occasions.MethodEighty adolescent students aged 15–18 years were randomized to one of three exercise intervention groups (endurance, strength, coordination) or to a non-exercise, control group. The exercise interventions lasted for 25 min. The random assignment to the study groups was stratified according to participants' age and gender. Before and after the exercise intervention, all participants completed the revised d2-test of attention. A 4 × 2 repeated measures ANOVA with contrast-coded test was used as the main analysis method.ResultsAttentional test performance increased from before to after the exercise intervention for all exercise groups, as compared with the control group. The three exercise groups improved equally and did not differ in their attentional scores after the intervention.ConclusionsAn acute bout of exercise was in general beneficial for adolescent students' attention, while the mode of the provided exercise training was not decisive. School directors and teachers are encouraged to incorporate exercise-related breaks into their school plan.     

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.