Literature DB >> 2343225

Receiver operator characteristic (ROC) curves and non-normal data: an empirical study.

M J Goddard1, I Hinberg.   

Abstract

This paper evaluates the performance of several diagnostic kits for assessing levels of serum prostatic acid phosphatase on patients at different stages of cancer of the prostate. Each patient was studied with several kits. We compare results obtained for receiver operator characteristic (ROC) curve methodology with data assumed to follow a normal distribution, with log-transformed data assumed to follow a normal distribution, and when neither of these assumptions holds. There were important differences between the results of the different approaches. For these data, the normal distribution assumption should be used with extreme caution. The log-transformed based results compared favourably with the non-parametric, but unconsidered application of the method should be avoided.

Entities:  

Mesh:

Substances:

Year:  1990        PMID: 2343225     DOI: 10.1002/sim.4780090315

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  16 in total

1.  Estimation of ROC curves based on stably distributed biomarkers subject to measurement error and pooling mixtures.

Authors:  Albert Vexler; Enrique F Schisterman; Aiyi Liu
Journal:  Stat Med       Date:  2008-01-30       Impact factor: 2.373

2.  Empirical-likelihood-based semiparametric inference for the treatment effect in the two-sample problem with censoring.

Authors:  Yong Zhou; Hua Liang
Journal:  Biometrika       Date:  2005-06-01       Impact factor: 2.445

3.  Semi-parametric hybrid empirical likelihood inference for two-sample comparison with censored data.

Authors:  Haiyan Su; Mai Zhou; Hua Liang
Journal:  Lifetime Data Anal       Date:  2011-03-12       Impact factor: 1.588

4.  A random-sum Wilcoxon statistic and its application to analysis of ROC and LROC data.

Authors:  Liansheng Larry Tang; N Balakrishnan
Journal:  J Stat Plan Inference       Date:  2010-06-12       Impact factor: 1.111

5.  Compare diagnostic tests using transformation-invariant smoothed ROC curves().

Authors:  Liansheng Tang; Pang Du; Chengqing Wu
Journal:  J Stat Plan Inference       Date:  2010-11-01       Impact factor: 1.111

6.  A semiparametric method for comparing the discriminatory ability of biomarkers subject to limit of detection.

Authors:  Lixuan Yin; Guoqing Diao; Aiyi Liu
Journal:  Stat Med       Date:  2017-07-25       Impact factor: 2.373

7.  Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray.

Authors:  Heng Zhu; Shaohui Hu; Ghil Jona; Xiaowei Zhu; Nate Kreiswirth; Barbara M Willey; Tony Mazzulli; Guozhen Liu; Qifeng Song; Peng Chen; Mark Cameron; Andrea Tyler; Jian Wang; Jie Wen; Weijun Chen; Susan Compton; Michael Snyder
Journal:  Proc Natl Acad Sci U S A       Date:  2006-03-07       Impact factor: 11.205

8.  Exact confidence interval estimation for the Youden index and its corresponding optimal cut-point.

Authors:  Chin-Ying Lai; Lili Tian; Enrique F Schisterman
Journal:  Comput Stat Data Anal       Date:  2010-12-07       Impact factor: 1.681

9.  Incidence and Risk Factors for Dysphagia Following Non-traumatic Subarachnoid Hemorrhage: A Retrospective Cohort Study.

Authors:  Katrina Dunn; Anna Rumbach
Journal:  Dysphagia       Date:  2018-08-07       Impact factor: 3.438

10.  Optimal sampling ratios in comparative diagnostic trials.

Authors:  Ting Dong; Liansheng Larry Tang; William F Rosenberger
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2014-04       Impact factor: 1.864

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.