Literature DB >> 29457474

The Importance of Calibration in Clinical Psychology.

Oliver Lindhiem1, Isaac T Petersen2, Lucas K Mentch1, Eric A Youngstrom3.   

Abstract

Accuracy has several elements, not all of which have received equal attention in the field of clinical psychology. Calibration, the degree to which a probabilistic estimate of an event reflects the true underlying probability of the event, has largely been neglected in the field of clinical psychology in favor of other components of accuracy such as discrimination (e.g., sensitivity, specificity, area under the receiver operating characteristic curve). Although it is frequently overlooked, calibration is a critical component of accuracy with particular relevance for prognostic models and risk-assessment tools. With advances in personalized medicine and the increasing use of probabilistic (0% to 100%) estimates and predictions in mental health research, the need for careful attention to calibration has become increasingly important.

Entities:  

Keywords:  accuracy; bias; calibration; confidence; forecasting; prediction; risk-assessment

Mesh:

Year:  2018        PMID: 29457474      PMCID: PMC6778000          DOI: 10.1177/1073191117752055

Source DB:  PubMed          Journal:  Assessment        ISSN: 1073-1911


  28 in total

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Review 3.  Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker.

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4.  A calibration hierarchy for risk models was defined: from utopia to empirical data.

Authors:  Ben Van Calster; Daan Nieboer; Yvonne Vergouwe; Bavo De Cock; Michael J Pencina; Ewout W Steyerberg
Journal:  J Clin Epidemiol       Date:  2016-01-06       Impact factor: 6.437

5.  Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): initial reliability and validity data.

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Journal:  J Am Acad Child Adolesc Psychiatry       Date:  1997-07       Impact factor: 8.829

6.  Use of Brier score to assess binary predictions.

Authors:  Kaspar Rufibach
Journal:  J Clin Epidemiol       Date:  2010-03-01       Impact factor: 6.437

7.  Evidence-Based Assessment from Simple Clinical Judgments to Statistical Learning: Evaluating a Range of Options Using Pediatric Bipolar Disorder as a Diagnostic Challenge.

Authors:  Eric A Youngstrom; Tate F Halverson; Jennifer K Youngstrom; Oliver Lindhiem; Robert L Findling
Journal:  Clin Psychol Sci       Date:  2017-12-08

8.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

9.  Comparing diagnostic checklists for pediatric bipolar disorder in academic and community mental health settings.

Authors:  Eric Youngstrom; Oren Meyers; Christine Demeter; Jen Youngstrom; Laura Morello; Richard Piiparinen; Norah Feeny; Joseph R Calabrese; Robert L Findling
Journal:  Bipolar Disord       Date:  2005-12       Impact factor: 6.744

10.  Quantifying diagnostic uncertainty using item response theory: the Posterior Probability of Diagnosis Index.

Authors:  Oliver Lindhiem; David J Kolko; Lan Yu
Journal:  Psychol Assess       Date:  2013-01-28
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Journal:  J Am Coll Emerg Physicians Open       Date:  2021-06-29
  10 in total

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