Abstract
The variance partition coefficient (VPC) measures the clustering of infection/disease among individuals with a specific covariate pattern. Covariate-pattern-specific VPCs provide insight to the groups of individuals that exhibit great heterogeneity and should be targeted for intervention. VPCs should be taken into consideration when planning study designs, modeling data and estimating sample sizes. We present a Bayesian discrete mixed model for the estimation of covariate-pattern-specific VPCs when measurement of the infection/disease is based on an imperfect test. The utility of the presented model is demonstrated with three applications. In all cases, imperfect tests biased VPC estimates towards the null but corrected estimates could be obtained by modeling the sensitivity and specificity of the test procedure with beta distributions. The comparison of adjusted VPCs between the intercept only and the fitted models with higher level covariates explained the portion of heterogeneity in the data that was accounted for by the covariates.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 155-162 |
| Number of pages | 8 |
| Journal | Preventive Veterinary Medicine |
| Volume | 89 |
| Issue number | 3-4 |
| DOIs | |
| State | Published - Jun 1 2009 |
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Keywords
- Bayesian estimation
- Paratuberculosis
- Salmonellosis
- Sensitivity
- Specificity
- Variance partition coefficient
ASJC Scopus subject areas
- Food Animals
- Animal Science and Zoology
Cite this
Bayesian estimation of variance partition coefficients adjusted for imperfect test sensitivity and specificity. / Kostoulas, Polychronis; Leontides, Leonidas; Browne, William J.; Gardner, Ian.
In: Preventive Veterinary Medicine, Vol. 89, No. 3-4, 01.06.2009, p. 155-162.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Bayesian estimation of variance partition coefficients adjusted for imperfect test sensitivity and specificity
AU - Kostoulas, Polychronis
AU - Leontides, Leonidas
AU - Browne, William J.
AU - Gardner, Ian
PY - 2009/6/1
Y1 - 2009/6/1
N2 - The variance partition coefficient (VPC) measures the clustering of infection/disease among individuals with a specific covariate pattern. Covariate-pattern-specific VPCs provide insight to the groups of individuals that exhibit great heterogeneity and should be targeted for intervention. VPCs should be taken into consideration when planning study designs, modeling data and estimating sample sizes. We present a Bayesian discrete mixed model for the estimation of covariate-pattern-specific VPCs when measurement of the infection/disease is based on an imperfect test. The utility of the presented model is demonstrated with three applications. In all cases, imperfect tests biased VPC estimates towards the null but corrected estimates could be obtained by modeling the sensitivity and specificity of the test procedure with beta distributions. The comparison of adjusted VPCs between the intercept only and the fitted models with higher level covariates explained the portion of heterogeneity in the data that was accounted for by the covariates.
AB - The variance partition coefficient (VPC) measures the clustering of infection/disease among individuals with a specific covariate pattern. Covariate-pattern-specific VPCs provide insight to the groups of individuals that exhibit great heterogeneity and should be targeted for intervention. VPCs should be taken into consideration when planning study designs, modeling data and estimating sample sizes. We present a Bayesian discrete mixed model for the estimation of covariate-pattern-specific VPCs when measurement of the infection/disease is based on an imperfect test. The utility of the presented model is demonstrated with three applications. In all cases, imperfect tests biased VPC estimates towards the null but corrected estimates could be obtained by modeling the sensitivity and specificity of the test procedure with beta distributions. The comparison of adjusted VPCs between the intercept only and the fitted models with higher level covariates explained the portion of heterogeneity in the data that was accounted for by the covariates.
KW - Bayesian estimation
KW - Paratuberculosis
KW - Salmonellosis
KW - Sensitivity
KW - Specificity
KW - Variance partition coefficient
UR - http://www.scopus.com/inward/record.url?scp=64949088214&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=64949088214&partnerID=8YFLogxK
U2 - 10.1016/j.prevetmed.2009.02.008
DO - 10.1016/j.prevetmed.2009.02.008
M3 - Article
C2 - 19297045
AN - SCOPUS:64949088214
VL - 89
SP - 155
EP - 162
JO - Preventive Veterinary Medicine
JF - Preventive Veterinary Medicine
SN - 0167-5877
IS - 3-4
ER -