The focus of this talk is dietary intervention trials. We will explore the statistical issues involved when the response variable, intake of a food or nutrient, is based on self-report data that are subject to inherent measurement error. There has been little work on handling error in this context. A particular feature of self-reported dietary intake data is that the error may be differential by intervention group. Measurement error methods require information on the nature of the errors in the self-report data, and we assume that there is a calibration sub-study in which unbiased biomarker data are available. I will outline methods for handling measurement error in this setting and use theory and simulations to show how self-report and biomarker data may be combined to estimate the intervention effect. Methods are illustrated using data from the Trial of Nonpharmacologic Intervention in the Elderly, in which the intervention was a sodium-lowering diet and the response was sodium intake.
Speaker: Ruth Keogh, London School of Hygiene & Tropical Medicine