Literature DB >> 20079947

Estimation of coefficients of individual agreement (CIAs) for quantitative and binary data using SAS and R.

Yi Pan1, Jingjing Gao, Michael Haber, Huiman X Barnhart.   

Abstract

The coefficients of individual agreement (CIAs), which are based on the ratio of the intra- and inter-observer disagreement, provide a general approach for evaluating agreement between two fixed methods of measurements or human observers. In this paper, programs in both SAS and R are presented for estimation of the CIAs between two observers with quantitative or binary measurements. A detailed illustration of the computations, macro variable definitions, input and output for the SAS and R programs are also included in the text. The programs provide estimations of CIAs, their standard errors as well as confidence intervals, for the cases with or without a reference method. Data from a carotid stenosis screening study is used as an example of quantitative measurements. Data from a study involving the evaluation of mammograms by ten radiologists is used to illustrate a binary data example. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20079947      PMCID: PMC2856751          DOI: 10.1016/j.cmpb.2009.12.002

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  17 in total

1.  Modeling concordance correlation via GEE to evaluate reproducibility.

Authors:  H X Barnhart; J M Williamson
Journal:  Biometrics       Date:  2001-09       Impact factor: 2.571

2.  A generalized concordance correlation coefficient for continuous and categorical data.

Authors:  T S King; V M Chinchilli
Journal:  Stat Med       Date:  2001-07-30       Impact factor: 2.373

3.  Overall concordance correlation coefficient for evaluating agreement among multiple observers.

Authors:  Huiman X Barnhart; Michael Haber; Jingli Song
Journal:  Biometrics       Date:  2002-12       Impact factor: 2.571

4.  Assessing the agreement between two quantitative assays with repeated measurements.

Authors:  Jun Shaoi; Bob Zhong
Journal:  J Biopharm Stat       Date:  2004-02       Impact factor: 1.051

5.  Assessing observer agreement in studies involving replicated binary observations.

Authors:  Michael Haber; Jingjing Gao; Huiman X Barnhart
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

6.  Resampling dependent concordance correlation coefficients.

Authors:  John M Williamson; Sara B Crawford; Hung-Mo Lin
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

7.  Assessing individual agreement.

Authors:  Huiman X Barnhart; Andrzej S Kosinski; Michael J Haber
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

8.  Comparison of concordance correlation coefficient and coefficient of individual agreement in assessing agreement.

Authors:  Huiman X Barnhart; Yuliya Lokhnygina; Andrzej S Kosinski; Michael Haber
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

9.  A general approach to evaluating agreement between two observers or methods of measurement from quantitative data with replicated measurements.

Authors:  Michael Haber; Huiman X Barnhart
Journal:  Stat Methods Med Res       Date:  2007-08-14       Impact factor: 3.021

10.  The intraclass correlation coefficient as a measure of reliability.

Authors:  J J Bartko
Journal:  Psychol Rep       Date:  1966-08
View more
  2 in total

1.  Using multiple agreement methods for continuous repeated measures data: a tutorial for practitioners.

Authors:  Richard A Parker; Charles Scott; Vanda Inácio; Nathaniel T Stevens
Journal:  BMC Med Res Methodol       Date:  2020-06-12       Impact factor: 4.615

2.  Influence of Weight-Age Normalization on Glomerular Filtration Rate Values of Renal Patients: A STROBE-Compliant Article.

Authors:  Li Li; Si Hongwei; Qiao Ying; Liu Jianzhong; Wu Zhifang; Gao Ling; Li Sijin
Journal:  Medicine (Baltimore)       Date:  2016-01       Impact factor: 1.817

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.