A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

Adam R. Brentnall; Stephen W. Duffy; Martin J. Crowder; Maureen G C Gillan; Susan M. Astley; Matthew G. Wallis; Jonathan James; Caroline R M Boggis; Fiona J. Gilbert

doi:10.1214/11-AOAS481

A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

Adam R. Brentnall, Stephen W. Duffy, Martin J. Crowder, Maureen G C Gillan, Susan M. Astley, Matthew G. Wallis, Jonathan James, Caroline R M Boggis, Fiona J. Gilbert

Research output: Contribution to journal › Article › peer-review

Abstract

When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis. © 2012 Institute of Mathematical Statistics.

Original language	English
Pages (from-to)	2448-2469
Number of pages	21
Journal	Annals of Applied Statistics
Volume	5
Issue number	4
DOIs	https://doi.org/10.1214/11-AOAS481
Publication status	Published - Dec 2011

Keywords

Classification
Computer-aided detection (CAD)
Likelihood
Mammogram
Random effects

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

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title = "A method for exploratory repeated-measures analysis applied to a breast-cancer screening study",

abstract = "When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis. {\textcopyright} 2012 Institute of Mathematical Statistics.",

keywords = "Classification, Computer-aided detection (CAD), Likelihood, Mammogram, Random effects",

author = "Brentnall, {Adam R.} and Duffy, {Stephen W.} and Crowder, {Martin J.} and Gillan, {Maureen G C} and Astley, {Susan M.} and Wallis, {Matthew G.} and Jonathan James and Boggis, {Caroline R M} and Gilbert, {Fiona J.}",

year = "2011",

month = dec,

doi = "10.1214/11-AOAS481",

language = "English",

volume = "5",

pages = "2448--2469",

journal = "Annals of Applied Statistics",

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publisher = "Institute of Mathematical Statistics",

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T1 - A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

AU - Brentnall, Adam R.

AU - Duffy, Stephen W.

AU - Crowder, Martin J.

AU - Gillan, Maureen G C

AU - Astley, Susan M.

AU - Wallis, Matthew G.

AU - James, Jonathan

AU - Boggis, Caroline R M

AU - Gilbert, Fiona J.

PY - 2011/12

Y1 - 2011/12

N2 - When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis. © 2012 Institute of Mathematical Statistics.

AB - When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis. © 2012 Institute of Mathematical Statistics.

KW - Classification

KW - Computer-aided detection (CAD)

KW - Likelihood

KW - Mammogram

KW - Random effects

U2 - 10.1214/11-AOAS481

DO - 10.1214/11-AOAS481

M3 - Article

SN - 1932-6157

VL - 5

SP - 2448

EP - 2469

JO - Annals of Applied Statistics

JF - Annals of Applied Statistics

IS - 4

ER -

A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

Abstract

Keywords

UN SDGs

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