Methodological considerations in the evaluation of the convergence of psychiatric diagnoses and parent-informant checklists

Psychiatric diagnoses and objective parent checklists are alternative ways to describe child adjustment problems. There has recently been interest in evaluating the degree of agreement or convergence between these sources of information. This paper addresses three issues neglected by researchers in this area. The appropriateness of the use of indices of sensitivity and specificity to describe the correspondence of diagnoses and checklist scores is questioned. Implications of failure to consider the reliability of diagnoses in interpreting diagnosis-checklist agreement are discussed. Also, possible parameters of diagnosis-checklist agreement that should be identified by researchers are reviewed. Suggestions for improving research in this area are offered.     

Age differences in target identification as a function of retinal location and noise level: examination of the useful field of view

Foveal and peripheral target detection were compared in young adults (M age = 22 years) and older adults (M age = 66 years) who were optically corrected for the viewing distance. In a two-alternative, forced-choice task, target letters were presented at 0 degree to 10.5 degrees from fixation. Targets were presented alone, flanked on each side by one noise element (i.e., nontarget letter), or embedded in a horizontal row of 19 noise elements. An Age X Noise Level X Location interaction was obtained, wherein age differences were largest for peripheral targets presented in noise. Slope analyses of latency data showed that the performance of young adults in the high-noise condition was most similar to that of older adults in the low-noise condition. At the functional level, results indicated that aging is associated with a restricted useful field of view. In addition, the data suggest that age differences in search can be described by a model in which older adults take smaller perceptual samples from the visual scene and scan these samples more slowly than do the young adults.     

The development of a child assessment interview for research and clinical use

The Child Assessment Schedule (CAS) was developed to address the need for a standardized child interview that could be used for research and clinical purposes. The CAS has several distinguishing characteristics: (1) Questions and responses are standardized, (2) the format was designed to enhance rapport with the child, and (3) information necessary for DSM III childhood diagnoses is explicitly solicited. The CAS was administered to 32 child outpatients, 18 inpatients, and 37 normal controls. Derived scores were obtained for total psychopathology, 11 content areas, and 9 symptom complexes. Interrater reliability for the total CAS score was quite high. The CAS was able to discriminate among the three groups in total score indicating degree of psychopathology, on 9 of the 11 content areas, and on 8 of the 9 symptom complexes. Significant correlations were found between the CAS and maternal report of child behavior and between the CAS and child selfreport of internal affects. It was concluded that the CAS has adequate reliability and validity, although further research is indicated.     

When Is a Parent Out of the Picture? Different Custody,Different Perceptions

This study investigated how 200 children from mother-, father-, or joint-custody arrangements perceived their divorced families. The authors argue that it is not the type of custody that shapes the child's view of whether one parent is peripheral but, rather, the nature of relationships within the various custody arrangements.     

How to Assess a Model's Testability and Identifiability

Formal definitions are given of the following intuitive concepts: (a) A model is quantitatively testable if its predictions are highly precise and narrow. (b) A model is identifiable if the values of its parameters can be ascertained from empirical observations. (c) A model is redundant if the values of some parameters can be deduced from others or if the values of some observables can be deduced from others. Various rules of thumb for nonredundant models are examined. The Counting Rule states that a model is quantitatively testable if and only if it has fewer parameters than observables. This rule can be safely applied only to identifiable models. If a model is unidentifiable, one must apply a generalization of the Counting Rule known as the Jacobian Rule. This rule states that a model is quantitatively testable if and only if the maximum rank (i.e., the number of linearly independent columns) of its Jacobian matrix (i.e., the matrix of partial derivatives of the function that maps parameter values to the predicted values of observables) is smaller than the number of observables. The Identifiability Rule states that a model is identifiable if and only if the maximum rank of its Jacobian matrix equals the number of parameters. The conclusions provided by these rules are only presumptive. To reach definitive conclusions, additional analyses must be performed. To illustrate the foregoing, the quantitative testability and identifiability of linear models and of discrete-state models are analyzed. Copyright 2000 Academic Press.