[R-sig-Epi] R-sig-Epi Digest, Vol 90, Issue 1

[Miguel Angel Luque Fernandez]

Dear all,
I am glad to be part of the list.

I am collaborating with academics in the States from the Harvard Medical School evaluating the performance (diagnosis accuracy) of a new biomarker for the diagnosis of Gestational Diabetes Mellitus.
http://care.diabetesjournals.org/content/early/2017/04/05/dc16-2598
However, the gold standard is imperfect (Oral glucose tolerance test), and we cannot get correct estimates of the AUC for the new biomarker.
Also, I thought about the evaluation of the performance in and independent sample size, which is not the standard case in medical studies, using cross-validation to adjust the value of the AUC
https://github.com/migariane/cvAUROC
However, I will be glad if any of you can refer to some seminal papers/references (in addition to the Pepe book) to illustrate how to implement the LCMATE analysis.
Thank you in advance for your time and help.
Kind regards,

Miguel Angel Luque Fernandez, PhD
Assistant Professor of Epidemiology and Biostatistics
London School of Hygiene and Tropical Medicine
London, UK



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Subject: R-sig-Epi Digest, Vol 90, Issue 1

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Today's Topics:

   1. LCMATE mailing list (Polychronis Kostoulas)


----------------------------------------------------------------------

Message: 1
Date: Wed, 3 May 2017 16:45:19 +0300
From: "Polychronis Kostoulas" <pkost at vet.uth.gr>
To: <r-sig-epi at r-project.org>
Subject: [R-sig-Epi] LCMATE mailing list
Message-ID: <000001d2c413$814fd080$83ef7180$@vet.uth.gr>
Content-Type: text/plain; charset="UTF-8"

Dear colleagues,



We have created LCMATE (Latent Class Models for the Accuracy of TEsts), a mailing list for people that are interested in the development and application of latent class models for the evaluation of diagnostic tests, primarily within a Bayesian framework. The focus is on estimating the diagnostic accuracy of tests (either dichotomous, ordinal or continuous) in the absence of a gold standard. LCMs are used within this context because the true disease status of the individuals/samples is unknown (i.e. latent, or hidden).



The scope of this list is to:

1. Assist researchers that are interested in the application of these methods to their own data

2. Promote the exchange of knowledge and ideas between researchers working in this area



To subscribe please visit:



http://lists.uth.gr/mailman/listinfo/lcmate



or send an email to:



lcmate-request at lists.uth.gr



Kind Regards,

Polychronis Kostoulas

LCMATE Administrator




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End of R-sig-Epi Digest, Vol 90, Issue 1