The data is obtained from a trial in which chronically ill mental health patients were randomized across two treatments: placebo and an active drug. A questionnaire instrument was used to assess each patient's mental state at weeks 0, 1, 2, 4, 6 and 8 post-randomisation, a high recorded score implying a severe condition. Some of the 100 patients dropped out of the study for reasons that were thought to be related to their mental state, and therefore potentially informative; others dropped out for reasons unrelated to their mental state.
data(mental)A balanced data set with respect to the times at which observations recorded. The data consists of the following variables on each patient:
idinteger: patient identifier.
Y.t0integer: mental state assessment in week 0. Coded
NA if missing.
Y.t1integer: mental state assessment in week 1. Coded
NA if missing.
Y.t2integer: mental state assessment in week 2. Coded
NA if missing.
Y.t4integer: mental state assessment in week 4. Coded
NA if missing.
Y.t6integer: mental state assessment in week 6. Coded
NA if missing.
Y.t8integer: mental state assessment in week 8. Coded
NA if missing.
treatinteger: treatment allocation. Coded as 0 =
placebo; 1 = active drug.
n.obsinteger: number of non-missing mental state assessments.
surv.timenumeric: imputed dropout time in weeks. Coded as
surv.time = 8.002 for completers.
cens.indinteger: censoring indicator. Coded as 0 =
completer or non-informative dropout; 1 = potentially informative
dropout.
Henderson R, Diggle PJ, Dobson A. Joint modelling of longitudinal measurements and event time data. Biostatistics. 2000; 1(4): 465-480.
Diggle PJ, Farewell D, Henderson R. Longitudinal data with dropout: objectives, assumptions and a proposal (with Discussion). Applied Statistics. 2007; 56: 499-550.
heart.valve, liver,
epileptic.