Effects of diagnostic classification systems on clinical hypothesis-generation

In this study it was determined whether (a) classification as opposed to absence of classification has an effect on the quality of clinical hypotheses (b) the DSM-III-R and the CBCL have a different effect on the quality of clinical hypotheses, and (c) the potential difference between the DSM-III-R and the CBCL is moderated by the different number of syndromes identified by these systems. To investigate these questions, an experiment was conducted in which 86 clinicians generated hypotheses for six cases. The clinicians were divided into a DSM-III-R, a CBCL, and a control group. Of the six cases, two were classified by both classification systems as one syndrome, two were classified as one syndrome by the DSM-III-R but as two syndromes by the CBCL, and two were classified as two syndromes by the DSM-III-R but as one syndrome by the CBCL. The quality of the hypotheses was determined by means of four dependent variables selected from an overview of qualitative criteria: explanatory value, redundancy, possibility of operationalization, and specificity. No differences between the CBCL and the control groups were found. The DSM group performed better than the control group regarding explanatory value and redundancy. The DSM-III-R group also scored better than the CBCL group regarding explanatory value, particularly when the number of identified syndromes was two for the CBCL and one for the DSM-III-R.     

A method for simulating non-normal distributions

A method of introducing a controlled degree of skew and kurtosis for Monte Carlo studies was derived. The form of such a transformation on normal deviates [X N(0, 1)] isY =a +bX +cX ² +dX ³. Analytic and empirical validation of the method is demonstrated.This work was done while the author was at the University of Illinois at Champaign-Urbana.     

A bayesian approach to confirmatory factor analysis

Confirmatory factor analysis is considered from a Bayesian viewpoint, in which prior information on parameter is incorporated in the analysis. An iterative algorithm is developed to obtain the Bayes estimates. A numerical example based on longitudinal data is presented. A simulation study is designed to compare the Bayesian approach with the maximum likelihood method.Computer facilities were provided by the Computer Services Center, The Chinese University of Hong Kong.     

Probability of directional errors with disordinal (qualitative) interaction

In a factorial design with two or more factors, there is nonzero interaction when the differences among the levels of one factor vary with levels of other factors. The interaction is disordinal or qualitative with respect to a specific factor, sayA, if the difference between at least two levels ofA is positive for some and negative for some levels of the other factors. Using standard methods of analysis, there is a potentially large probability of drawing incorrect conclusions about the signs of differences in the presence of disordinal interaction. The maximum probability of such incorrect conclusions, or directional errors, is derived for two-factor designs in which the factor of interest has two levels and the number of levels of the other factor varies.     

MODIFICATION OF THE EXCESSIVE INAPPROPRIATE CLASSROOM BEHAVIOR OF TWO ELEMENTARY SCHOOL STUDENTS USING HOME-BASED CONSEQUENCES AND DAILY REPORT-CARD PROCEDURES1

Two experiments investigated home-based reinforcement contingencies to control excessive behavior in normal classrooms. Subjects were, respectively, a 12-yr-old fifth-grade boy and a 9-yr-old fourth-grade boy, each in a separate classroom and with a different teacher. Following baseline observations in which observers recorded several categories of student behavior and teacher-student interaction, separate conferences were held including parents of the two children, the principal, teachers, and experimenters. A daily report-card procedure was agreed on, stipulating a one-day suspension from school following three successive “undesirable” daily report cards as well as the supervision of home-based privileges and other reinforcers usually contingent on satisfactory daily reports. Measurements of daily rates of teacher attention indicated no important change in this variable throughout the various experimental conditions. The daily report procedure significantly reduced disruptive classroom behavior. In a second experiment, a teacher-operated timer cued her own time-sample observations. Reliability measures revealed that the teacher could accurately measure the child's behavior while she was teaching the class. The procedure was ultimately successfully expanded to the teacher's total contact hours each day.     

Changes in Children's Episodic Narratives Through Long-Term Repeated Recall: Longitudinal Case Studies1

This study aimed to investigate whether a child's narrative of a particular past episode would change in repeated reporting over the long term, and if so, how it would change. To answer these questions, I conducted longitudinal case studies of episodic reports by children every 2–6 months, from their early childhood to the age of 10–15 years. Criteria for inclusion were set in advance; seven episodic narratives meeting these criteria were analyzed. Two types of changes in the narratives were observed, as expected: that of including other information, and that of an event suddenly being reported after no recall for several years. Information from the children's surroundings seemed to be substantially involved in these changes in their episodic narratives. The present results also indicate that mothers' episodic memories are not always reliable and that the schema children have can influence their episodic memories.