Epidemiology & Biostatistics

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Subject: search.filters.subject.Health Sciences, Public Health

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    DIAGNOSTICS FOR MULTIPLE IMPUTATION BASED ON THE PROPENSITY SCORE
    (2010) Wang, Jia; Zhang, Guangyu; Epidemiology and Biostatistics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Multiple imputation (MI) is a popular approach to handling missing data, however, there has been limited work on diagnostics of imputation results. We propose two diagnostic techniques for imputations based on the propensity score (1) compare the conditional distributions of observed and imputed values given the propensity score; (2) fit regression models of the imputed data as a function of the propensity score and the missing indicator. Simulation results show these diagnostic methods can identify the problems relating to the imputations given the missing at random assumption. We use 2002 US Natality public-use data to illustrate our method, where missing values in gestational age and in covariates are imputed using Sequential Regression Multiple Imputation method.
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    Association between Allostatic Load and Arthritis in NHANES Adults
    (2010) Scully, Lynn; Lee, Sunmin; Epidemiology and Biostatistics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Objective: To examine the cross-sectional association between allostatic load and arthritis using data from the National Health and Nutrition Examination Survey (NHANES). Methods: Complete data on 7,714 adults were included in the analysis. An allostatic load (AL) index, comprising of multiple regulatory systems, was calculated from 11 biomarkers. Multivariate logistic regression was used to estimate the odds ratio (OR) for the association between allostatic load and arthritis, while accounting for confounders. Results: Significant positive associations were found between both continuous allostatic load (OR=1.12, 95% CI= 1.08-1.17) and the two highest quartile categories of AL and arthritis compared to the lowest quartile (quartile 3: OR=1.73, 95% CI=1.38-2.17, quartile 4: OR=1.79, 95% CI=1.41-2.26), after adjusting for confounders. The subscales of the inflammatory (OR=1.27, 95% CI=1.15-1.40) and metabolic system (OR=1.20, 95% CI=1.13-1.28) were also significant predictors. Conclusions: Cumulative biological risk is a plausible mechanism that is associated with arthritis.