title: A modelling approach to the analysis of menstrual diary data.
abstract: In clinical trials to compare contraceptives, women are usually asked to record whether or not each day is a bleeding day over the duration of the trial. In this paper we describe how parametric models, which include terms corresponding to covariates recorded for each woman, can be used to analyse data on the occurrence of certain adverse events identified from the diary record. Linear logistic models are used to analyse the probability of prolonged bleeding or amenorrhoea, and log-linear models are used to analyse the lengths of bleeding episodes. In both cases variation between women is allowed for by including a random effect in the model. The application of our methods is illustrated using a data base made available by the World Health Organization.
authors.affiliation: Department of Applied Statistics, University of Reading, U.K.
authors.forename: D
authors.initials: D
authors.lastname: Collett
authors.forename: N
authors.initials: N
authors.lastname: Weerasooriya
mesh_terms: D015982:Bias; D002986:Clinical Trials as Topic; D003267:Contraception / Q000009:adverse effects* / Q000379:methods; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D005260:Female; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008499:Medical Records; D017258:Medroxyprogesterone Acetate / Q000009:adverse effects; D008599:Menstruation Disturbances / Q000139:chemically induced / Q000453:epidemiology*; D015233:Models, Statistical; D012016:Reference Values
chemical_list: D017258:Medroxyprogesterone Acetate