title: Measurement error models for ordinal exposure variables measured with error.
abstract: In dietary epidemiology, the key nutrient variables are often expressed in the quintile scale. The nutrients are often measured with error and it is of interest to consider estimates of relative risk for exposures in the quintile scale corrected for measurement error. In this paper, I propose a measurement error model that relates diet record (true) nutrient values to food frequency (noisy) nutrient values when expressed in the quintile scale. I estimate this measurement error model from validation study data and then apply it to obtain corrected estimates of breast cancer risk in relation to intake of fat and alcohol with use of data from the Nurses' Health Study.
authors.affiliation: Channing Laboratory, Brigham and Women's Hospital, Boston, MA 02115, USA.
authors.forename: B A
authors.initials: BA
authors.lastname: Rosner
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000428:Alcohol Drinking / Q000009:adverse effects*; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000209:etiology; D015930:Diet Records; D004041:Dietary Fats / Q000009:adverse effects*; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D012306:Risk; D014481:United States
chemical_list: D004041:Dietary Fats