A multilevel model for spatially correlated binary data in the presence of misclassification: an application in oral health research. (29th August 2013)
- Record Type:
- Journal Article
- Title:
- A multilevel model for spatially correlated binary data in the presence of misclassification: an application in oral health research. (29th August 2013)
- Main Title:
- A multilevel model for spatially correlated binary data in the presence of misclassification: an application in oral health research
- Authors:
- Mutsvari, Timothy
Bandyopadhyay, Dipankar
Declerck, Dominique
Lesaffre, Emmanuel
Aalen, Odd O.
Borgan, Ørnulf
Kvaløy, Jan Terje - Abstract:
- <abstract abstract-type="main" id="sim5944-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Dental caries is a highly prevalent disease affecting the tooth's hard tissues by acid‐forming bacteria. The past and present caries status of a tooth is characterized by a response called caries experience (CE). Several epidemiological studies have explored risk factors for CE. However, the detection of CE is prone to misclassification because some cases are neither clearly carious nor noncarious, and this needs to be incorporated into the epidemiological models for CE data. From a dentist's point of view, it is most appealing to analyze CE on the tooth's surface, implying that the multilevel structure of the data (surface–tooth–mouth) needs to be taken into account. In addition, CE data are spatially referenced, that is, an active lesion on one surface may impact the decay process of the neighboring surfaces, and that might also influence the process of scoring CE. In this paper, we investigate two hypotheses: that is, (i) CE outcomes recorded at surface level are spatially associated; and (ii) the dental examiners exhibit some spatial behavior while scoring CE at surface level, by using a spatially referenced multilevel autologistic model, corrected for misclassification. These hypotheses were tested on the well‐known Signal Tandmobiel® study on dental caries, and simulation studies were conducted to assess the effect of misclassification and strength of spatial<abstract abstract-type="main" id="sim5944-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Dental caries is a highly prevalent disease affecting the tooth's hard tissues by acid‐forming bacteria. The past and present caries status of a tooth is characterized by a response called caries experience (CE). Several epidemiological studies have explored risk factors for CE. However, the detection of CE is prone to misclassification because some cases are neither clearly carious nor noncarious, and this needs to be incorporated into the epidemiological models for CE data. From a dentist's point of view, it is most appealing to analyze CE on the tooth's surface, implying that the multilevel structure of the data (surface–tooth–mouth) needs to be taken into account. In addition, CE data are spatially referenced, that is, an active lesion on one surface may impact the decay process of the neighboring surfaces, and that might also influence the process of scoring CE. In this paper, we investigate two hypotheses: that is, (i) CE outcomes recorded at surface level are spatially associated; and (ii) the dental examiners exhibit some spatial behavior while scoring CE at surface level, by using a spatially referenced multilevel autologistic model, corrected for misclassification. These hypotheses were tested on the well‐known Signal Tandmobiel® study on dental caries, and simulation studies were conducted to assess the effect of misclassification and strength of spatial dependence on the autologistic model parameters. Our results indicate a substantial spatial dependency in the examiners' scoring behavior and also in the prevalence of CE at surface level. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract> … (more)
- Is Part Of:
- Statistics in medicine. Volume 32:Number 30(2013)
- Journal:
- Statistics in medicine
- Issue:
- Volume 32:Number 30(2013)
- Issue Display:
- Volume 32, Issue 30 (2013)
- Year:
- 2013
- Volume:
- 32
- Issue:
- 30
- Issue Sort Value:
- 2013-0032-0030-0000
- Page Start:
- 5241
- Page End:
- 5259
- Publication Date:
- 2013-08-29
- Subjects:
- Medical statistics -- Periodicals
Statistique médicale -- Périodiques
Statistiques médicales -- Périodiques
610.727 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/sim.5944 ↗
- Languages:
- English
- ISSNs:
- 0277-6715
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8453.576000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 4131.xml