Presence of Bacteria after Drug Treatments

DESCRIPTION:

Tests of the presence of the bacteria H. influenzae in children with otitis media in the Northern Territory of Australia.

DATA DESCRIPTION:

This data frame has 220 rows and the following columns:

ARGUMENTS:

y
presence or absence: a factor with levels y and n.
ap
active/placebo: a factor with levels a and p.
hilo
hi/low compliance: a factor with levels hi and lo.
week
numeric: week of test.
ID
subject ID: a factor.
trt
factor with levels placebo, drug and drug+, a re-coding of ap and hilo.

DETAILS:

Dr A. Leach tested the effects of a drug on 50 children with a history of otitis media in the Northern Territory of Australia. The children were randomized to the drug or the a placebo, and also to receive active encouragement to comply with taking the drug. The presence of H. influenzae was checked at weeks 0, 2, 4, 6 and 11: 30 of the checks were missing and are not included in this data frame.

SOURCE:

Menzies School of Health Research 1999-2000 Annual Report pp. 18-21 http://www.menzies.edu.au/publications/anreps/MSHR00.pdf.

EXAMPLES:

contrasts(bacteria$trt) <- structure(contr.sdif(3),
     dimnames = list(NULL, c("drug", "encourage")))
## fixed effects analyses
summary(glm(y ~ trt * week, binomial, data = bacteria))
summary(glm(y ~ trt + week, binomial, data = bacteria))
summary(glm(y ~ trt + I(week > 2), binomial, data = bacteria))
# conditional random-effects analysis
bacteria$Time <- rep(1, nrow(bacteria))
coxph(Surv(Time, unclass(y)) ~ week + strata(ID),
      data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ factor(week) + strata(ID),
      data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ I(week > 2) + strata(ID),
      data = bacteria, method = "exact")
# PQL glmm analysis
summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID,
                family = binomial, data = bacteria))