Analysis of a marker for cancer of the thyroid with a limit of detection
File(s)
Accepted version
Author(s)
Longford, NT
Tovar Cuevas, JR
Alvear, C
Type
Journal Article
Abstract
Limit of detection (LoD) is a common problem in the analysis of data
generated by instruments that cannot detect very small concentra-
tions or other quantities, resulting in left-censored measurements.
Methods intended for data that are not subject to this problem are
often difficult to modify for censoring. We adapt the simulation-
extrapolation method, devised originally for fitting models with
measurement error, to dealing with LoD in conjunction with a mix-
ture analysis. The application relates the levels of thyroglobulin in
individuals with cancer of the thyroid before and after treatment
with radioactive iodine I–131. We conclude that the fitted mixture
components correspond to levels of effectiveness of the treatment.
generated by instruments that cannot detect very small concentra-
tions or other quantities, resulting in left-censored measurements.
Methods intended for data that are not subject to this problem are
often difficult to modify for censoring. We adapt the simulation-
extrapolation method, devised originally for fitting models with
measurement error, to dealing with LoD in conjunction with a mix-
ture analysis. The application relates the levels of thyroglobulin in
individuals with cancer of the thyroid before and after treatment
with radioactive iodine I–131. We conclude that the fitted mixture
components correspond to levels of effectiveness of the treatment.
Date Issued
2017-01-01
Date Acceptance
2016-10-20
Citation
Journal of Applied Statistics, 2017, 44 (12), pp.2190-2203
ISSN
1360-0532
Publisher
Taylor & Francis (Routledge)
Start Page
2190
End Page
2203
Journal / Book Title
Journal of Applied Statistics
Volume
44
Issue
12
Copyright Statement
© 2016 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis inJournal of Applied Statistics on 24 Oct 2016, available online: https://www.tandfonline.com/doi/full/10.1080/02664763.2016.1247792
Subjects
Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
Cancer
extrapolation
limit of detection
mixture model
thyroid
MAXIMUM-LIKELIHOOD
EM ALGORITHM
THERAPY
EXTRAPOLATION
PERFORMANCE
CARCINOMA
SUBJECT
0104 Statistics
Publication Status
Published
Date Publish Online
2016-10-24