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Biomedical subjects

William M Grove

Publications and source records attributed to William M Grove.

8 recordsLinked to original sources
PubMed2006

Meehl's contribution to clinical versus statistical prediction.

Paul E. Meehl's work on the clinical versus statistical prediction controversy is reviewed. His contributions included the following: putting the controversy center stage in applied psychology; clarifying concepts underpinning the debate (especially his crucial distinction between ways of gathering data and ways of combining them) as well as establishing that the controversy was real and not concocted, analyzing clinical inference from both theoretical and probabilistic points of view, and reviewing studies that compared the accuracy of these 2 methods of data combination. Meehl's (1954/1996) conclusion that statistical prediction consistently outperforms clinical judgment has stood up extremely well for half a century. His conceptual analyses have not been significantly improved since he published them in the 1950s and 1960s. His work in this area contains several citation classics, which are part of the working knowledge of all competent applied psychologists today.

Famous Persons↗
PubMed2006

Meehl as colleague.

The author summarizes some memories and impressions of Paul Meehl as graduate advisor, classroom teacher, and departmental colleague.

Famous Persons↗
PubMed2005

Clinical versus statistical prediction: the contribution of Paul E. Meehl.

The background of Paul E. Meehl's work on clinical versus statistical prediction is reviewed, with detailed analyses of his arguments. Meehl's four main contributions were the following: (a) he put the question, of whether clinical or statistical combinations of psychological data yielded better predictions, at center stage in applied psychology; (b) he convincingly argued, against an array of objections, that clinical versus statistical prediction was a real (not concocted) problem needing thorough study; (c) he meticulously and even-handedly dissected the logic of clinical inference from theoretical and probabilistic standpoints; and (c) he reviewed the studies available in 1954 and thereafter, which tested the validity of clinical versus statistical predictions. His early conclusion that the literature strongly favors statistical prediction has stood up extremely well, and his conceptual analyses of the prediction problem (especially his defense of applying aggregate-based probability statements to individual cases) have not been significantly improved since 1954.

Forecasting↗
PubMed2004

Antisaccade performance is impaired in medically and psychiatrically healthy biological relatives of schizophrenia patients.

Schizophrenia patients and their relatives have been found to exhibit increased reflexive errors on the antisaccade task, suggesting the deficit reflects genetic susceptibility for schizophrenia. To evaluate the degree to which antisaccade error is elevated in schizophrenia relatives, we carried out a meta-analysis of the existing literature and a primary study examining whether the magnitude of reported differences between relative and nonpsychiatric comparison groups could be due to differences in participant inclusion criteria. Meta-analysis yielded a moderate to large effect size across studies comparing relatives and controls (Cohen's d=0.61; Glass' d(g)=0.87). Antisaccade performance in medically and psychiatrically healthy relatives (n=45), who were selected from a larger sample of relatives based on criteria applied to healthy controls, was significantly more impaired than in healthy control participants (d=0.81, d(g)=0.93). Moreover, excluded (n=71) and included relatives did not differ (d=0.14, d(g)=0.13). The results indicate that the antisaccade deficit is a robust phenomenon in unaffected schizophrenia relatives that is not due to differences in inclusion criteria between relatives and controls, and thus are consistent with a growing literature indicating that the antisaccade deficit will be a valuable endophenotype of schizophrenia.

Adolescent↗
PubMed2004

Multiple dimensions of schizotypy in first degree biological relatives of schizophrenia patients.

Considerable research has been devoted to identifying individuals predisposed to schizophrenia, with much of the effort devoted to identifying the personality characteristics of the biological relatives of schizophrenia patients. Although resource-consuming interviews have yielded promising results, investigators have long sought self-report measures that index genetic risk for schizophrenia. The Schizotypal Personality Questionnaire (SPQ) is a self-report measure that assesses the nine features of DSM-defined schizotypy. The SPQ, modified to include validity scales, was administered to 135 nonpsychotic first degree relatives of schizophrenia patients and 112 healthy controls. Principal components analysis (PCA) yielded three factors that correlated highly with previously reported factors (social-interpersonal, cognitive-perceptual, and disorganization). Social-interpersonal deficits were found to best differentiate relatives from controls. Contrary to the hypothesis that schizophrenia relatives are more defensive in responding to schizotypy questionnaires, relatives were significantly less defensive than controls. The results demonstrate that a multidimensional paper-and-pencil measure can characterize schizotypal features in schizophrenia relatives, which will be useful for the further delineation of the heritable schizophrenia spectrum phenotype.

Child↗
PubMed2004

The maxslope taxometric procedure: mathematical derivation, parameter estimation, consistency tests.

This article first explains concepts in taxometrics, including the meaning of "taxon" in relation to taxometric procedures. It then mathematically develops the MAXSLOPE procedure of Grove and Meehl which relies on nonlinear regression of one taxometric indicator variable on another. Sufficient conditions for MAXSLOPE's validity are set forth. The relationship between the point of maximum regression slope (MAXSLOPE point) and the HITMAX cut, i.e., the point on a variable which, if used as a diagnostic cut-off score, yields maximum classification accuracy, is analyzed. A sufficient condition is given for the MAXSLOPE point to equal the HITMAX cut; however, most distributions have different MAXSLOPE and HITMAX points. Equations and an algorithm are spelled out for making a graphical test for the existence of a taxon, estimating taxometric parameters, and conducting consistency tests; the latter serve as stringent checks on the validity of a taxonic conjecture. The plausibility of assumptions made, in deriving MAXSLOPE equations, is discussed, and the qualitative effects of violations of these assumptions are explained.

Classification↗