Exposure misclassification from area sampling in epidemiologic studies of cookstove emissions

Bayesian adjustment for exposure misclassification in case-control studies.

Poor measurement of explanatory variables occurs frequently in observational studies. Error-prone observations may lead to biased estimation and loss of power in detecting the impact of explanatory variables on the response. We consider misclassified binary exposure in the context of case-control studies, assuming the availability of validation data to inform the magnitude of the misclassificat...

Correct sampling in observational studies.

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Social, Economic, and Resource Predictors of Variability in Household Air Pollution from Cookstove Emissions

We examine if social and economic factors, fuelwood availability, market and media access are associated with owning a modified stove and variation in household emissions from biomass combustion, a significant environmental and health concern in rural India. We analyze cross-sectional household socio-economic data, and PM(2.5) and particulate surface area concentration in household emissions fr...

Accounting for response misclassification and covariate measurement error improves power and reduces bias in epidemiologic studies.

PURPOSE To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. METHODS A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between an...

Global radiative effects of solid fuel cookstove aerosol emissions