Literature DB >> 21673222

Patient self-report and medical records: measuring agreement for binary data.

Angela M Barbara1, Mark Loeb, Lisa Dolovich, Kevin Brazil, Margaret L Russell.   

Abstract

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Year:  2011        PMID： 21673222      PMCID： PMC3114683     

Source DB:  PubMed          Journal:  Can Fam Physician        ISSN： 0008-350X            Impact factor:   3.275


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  13 in total

Review 1.  The kappa statistic in reliability studies: use, interpretation, and sample size requirements.

Authors:  Julius Sim; Chris C Wright
Journal:  Phys Ther       Date:  2005-03

2.  Statistical methods for assessing observer variability in clinical measures.

Authors:  P Brennan; A Silman
Journal:  BMJ       Date:  1992-06-06

3.  High agreement but low kappa: II. Resolving the paradoxes.

Authors:  D V Cicchetti; A R Feinstein
Journal:  J Clin Epidemiol       Date:  1990       Impact factor: 6.437

4.  Behavior and interpretation of the kappa statistic: resolution of the two paradoxes.

Authors:  C A Lantz; E Nebenzahl
Journal:  J Clin Epidemiol       Date:  1996-04       Impact factor: 6.437

5.  The dependence of kappa on attribute prevalence when assessing the repeatability of questionnaire data.

Authors:  J M Sargeant; S W Martin
Journal:  Prev Vet Med       Date:  1998-02-27       Impact factor: 2.670

6.  A reappraisal of the kappa coefficient.

Authors:  W D Thompson; S D Walter
Journal:  J Clin Epidemiol       Date:  1988       Impact factor: 6.437

7.  High agreement but low kappa: I. The problems of two paradoxes.

Authors:  A R Feinstein; D V Cicchetti
Journal:  J Clin Epidemiol       Date:  1990       Impact factor: 6.437

8.  The measurement of observer agreement for categorical data.

Authors:  J R Landis; G G Koch
Journal:  Biometrics       Date:  1977-03       Impact factor: 2.571

9.  Bias, prevalence and kappa.

Authors:  T Byrt; J Bishop; J B Carlin
Journal:  J Clin Epidemiol       Date:  1993-05       Impact factor: 6.437

10.  Comparison of self-report data and medical records data: results from a case-control study on prostate cancer.

Authors:  K Zhu; B McKnight; A Stergachis; J R Daling; R S Levine
Journal:  Int J Epidemiol       Date:  1999-06       Impact factor: 7.196
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  6 in total

1.  Identifying Patient Readmissions: Are Our Data Sources Misleading?

Authors:  Andrea E Daddato; Blythe Dollar; Hillary D Lum; Robert E Burke; Rebecca S Boxer
Journal:  J Am Med Dir Assoc       Date:  2019-06-18       Impact factor: 4.669

2.  The Gynaecologic Leiden Questionnaire: psychometric properties of a self-report questionnaire of sexual function and vaginal changes for gynaecological cancer patients.

Authors:  Q D Pieterse; M M Ter Kuile; C P Maas; G G Kenter
Journal:  Psychooncology       Date:  2008-07       Impact factor: 3.894

3.  Convergent Validity of Three Methods for Measuring Postoperative Complications.

Authors:  Bradley A Fritz; Krisztina E Escallier; Arbi Ben Abdallah; Jordan Oberhaus; Jennifer Becker; Kristin Geczi; Sherry McKinnon; Dan L Helsten; Anshuman Sharma; Troy S Wildes; Michael S Avidan
Journal:  Anesthesiology       Date:  2016-06       Impact factor: 7.892

4.  Calculations of Financial Incentives for Providers in a Pay-for-Performance Program: Manual Review Versus Data From Structured Fields in Electronic Health Records.

Authors:  Tracy H Urech; LeChauncy D Woodard; Salim S Virani; R Adams Dudley; Meghan Z Lutschg; Laura A Petersen
Journal:  Med Care       Date:  2015-10       Impact factor: 2.983

5.  Concordance between medical records and interview data in correctional facilities.

Authors:  Jennifer R Bai; Dhritiman V Mukherjee; Montina Befus; Zoltan Apa; Franklin D Lowy; Elaine L Larson
Journal:  BMC Med Res Methodol       Date:  2014-04-09       Impact factor: 4.615

6.  Comparative evaluation of a two-reagent cold stain method with Ziehl-Nelseen method for pulmonary tuberculosis diagnosis.

Authors:  Yemane Weldu; Daniel Asrat; Yimtubezinash Woldeamanuel; Aregawi Hailesilasie
Journal:  BMC Res Notes       Date:  2013-08-13
  6 in total

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