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A moment-adjusted imputation method for measurement error models.

ABSTRACT: Studies of clinical characteristics frequently measure covariates with a single observation. This may be a mismeasured version of the "true" phenomenon due to sources of variability like biological fluctuations and device error. Descriptive analyses and outcome models that are based on mismeasured data generally will not reflect the corresponding analyses based on the "true" covariate. Many statistical methods are available to adjust for measurement error. Imputation methods like regression calibration and moment reconstruction are easily implemented but are not always adequate. Sophisticated methods have been proposed for specific applications like density estimation, logistic regression, and survival analysis. However, it is frequently infeasible for an analyst to adjust each analysis separately, especially in preliminary studies where resources are limited. We propose an imputation approach called moment-adjusted imputation that is flexible and relatively automatic. Like other imputation methods, it can be used to adjust a variety of analyses quickly, and it performs well under a broad range of circumstances. We illustrate the method via simulation and apply it to a study of systolic blood pressure and health outcomes in patients hospitalized with acute heart failure.

SUBMITTER: Thomas L

PROVIDER: S-EPMC3208089 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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A moment-adjusted imputation method for measurement error models.

Thomas Laine L Stefanski Leonard L Davidian Marie M

Biometrics 20110308 4

Studies of clinical characteristics frequently measure covariates with a single observation. This may be a mismeasured version of the "true" phenomenon due to sources of variability like biological fluctuations and device error. Descriptive analyses and outcome models that are based on mismeasured data generally will not reflect the corresponding analyses based on the "true" covariate. Many statistical methods are available to adjust for measurement error. Imputation methods like regression cali ...[more]

PMID: 21385161

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Project description:Echinococcosis is a major emerging zoonosis in central Asia. A cross-sectional study of dogs in four villages in rural Kyrgyzstan was undertaken to investigate the epidemiology and transmission of Echinococcus spp. A total of 466 dogs were examined by arecoline purgation for the presence of Echinococcus granulosus and E. multilocularis. In addition, a faecal sample from each dog was examined for taeniid eggs. Any taeniid eggs found were investigated using PCR techniques (multiplex and single target PCR) to improve the diagnostic sensitivity by confirming the presence of Echinococcus spp. and to identify E. granulosus strains. A total of 83 (18%) dogs had either E. granulosus adults in purge material and/or E. granulosus eggs in their faeces as confirmed by PCR. Three genotypes of E. granulosus: G1, G4 and the G6/7 complex were shown to be present in these dogs through subsequent sequence analysis. Purge analysis combined with PCR identified 50 dogs that were infected with adult E. multilocularis and/or had E. multilocularis eggs in their faeces (11%). Bayesian techniques were employed to estimate the true prevalence, the diagnostic sensitivity and specificity of the procedures used and the transmission parameters. The sensitivity of arecoline purgation for the detection of echinococcosis in dogs was rather low, with a value of 38% (credible intervals (CIs) 27-50%) for E. granulosus and 21% (CIs 11-34%) for E. multilocularis. The specificity of arecoline purgation was assumed to be 100%. The sensitivity of coproscopy followed by PCR of the isolated eggs was calculated as 78% (CIs 57-87%) for E. granulosus and 50% (CIs 29-72%) for E. multilocularis with specificity of 93% (CIs 88-96%) and 100% (CIs 97-100%), respectively. The 93% specificity of the coprological-PCR for E. granulosus could suggest coprophagia rather than true infections. After adjusting for the sensitivity of the diagnostic procedures, the estimated true prevalence of infection of E. granulosus was 19% (CIs 15-25%) and the infection pressure in the dog population was estimated to be 0.29 infections per year (CIs 0.014-0.75). Logistic regression analysis failed to identify any significant risk factors for infections for E. granulosus. After adjusting for the sensitivity of the test procedures, the estimated true prevalence for E. multilocularis was 18% (CIs 12-30%). Dogs that were restrained had a significantly lower prevalence of E. multilocularis of 11% (CIs 6-29%) compared with 26% in free-roaming dogs (CIs 17-44%) and independently within these groups hunting dogs were more likely to be infected than non-hunting dogs.

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A moment-adjusted imputation method for measurement error models.

Publications

A moment-adjusted imputation method for measurement error models.

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