1990
DOI: 10.1016/0022-3956(90)90002-8
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Using signal detection methodology to revise DSM-III-R: Re-analysis of the DSM-III-R national field trials for autistic disorder

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Cited by 30 publications
(13 citation statements)
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“…After the latent class model is applied to empirical selection of a "gold standard" against which a set of diagnostic COMPLICATED GRIEF criteria may be calibrated, signal detection analyses can be applied to select specific items to serve as diagnostic criteria. The mathematics of the signal detection method has been described for psychiatric applications (38) and has already been used to model DSM-like sets of diagnostic criteria (39)(40)(41). In the signal detection method, it is possible to enter a series of predictors (possible diagnostic criteria) simultaneously and then to pick the predictors that correspond to the highest total predictive value, while monitoring the need to identify further predictors for cases that have not yet been "diagnosed" by the existing algorithm.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…After the latent class model is applied to empirical selection of a "gold standard" against which a set of diagnostic COMPLICATED GRIEF criteria may be calibrated, signal detection analyses can be applied to select specific items to serve as diagnostic criteria. The mathematics of the signal detection method has been described for psychiatric applications (38) and has already been used to model DSM-like sets of diagnostic criteria (39)(40)(41). In the signal detection method, it is possible to enter a series of predictors (possible diagnostic criteria) simultaneously and then to pick the predictors that correspond to the highest total predictive value, while monitoring the need to identify further predictors for cases that have not yet been "diagnosed" by the existing algorithm.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…This procedure simultaneously optimizes sensitivity a nd spec ificity a nd iden tifi es t he single crite rion with th e highest total pr edi ctiv e valu e. In other words, t his p roced ur e att empts to determin e how well a single sign or symptom performs in iden tifying a syndrome in contrast to identifying all th e elements of th at syndrom e. In th e cas e of autism, th ey wanted to det ermine whi ch of th e 16 diagnosti c crite ria of DSM-III we re most frequently evalua te d as central to the diagnosis. The di agn ostic cr iteria described as "marked lack of awareness of th e existe nce or feelings of ot hers," perform ed as well as th e combination of criteria recommended by DSM-III-R. T he second crite ria with th e next highest total predi ctive valu e was " pe rs iste nt pr eoccupation with parts of obj ects " (18). The data collec te d for th e DSM-III-R field trials for autistic disorder were re-anal yzed using signal d etecti on me th ods (18 ).…”
Section: Signal Detectionmentioning
confidence: 99%
“…The di agn ostic cr iteria described as "marked lack of awareness of th e existe nce or feelings of ot hers," perform ed as well as th e combination of criteria recommended by DSM-III-R. T he second crite ria with th e next highest total predi ctive valu e was " pe rs iste nt pr eoccupation with parts of obj ects " (18). The data collec te d for th e DSM-III-R field trials for autistic disorder were re-anal yzed using signal d etecti on me th ods (18 ). Findings support inclusion of on e diagnostic crite rion ("marked lack of awaren ess of others ") as mandatory, and four more (im pa ire d imit ation , a bnormal soc ial play, abnormal nonverbal communication , a nd abnormal speech) as a lterna te, associa ted crite ria (18).…”
Section: Signal Detectionmentioning
confidence: 99%
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