Thall: RCT on the treatment of epilepsy.

In pubh: A Toolbox for Public Health and Epidemiology

RCT on the treatment of epilepsy.

Description

Randomised control trial of an antiepilectic drug (prograbide), in which the number of seizures of 59 patients at baseline and other four follow-up visits were recorded.

Usage

Thall

Format

A tibble with 59 rows and 8 variables:

id

Subject ID.

treat

Treatment, factor with levels "Control" and "Prograbide".

base

Number of seizures at baseline.

age

Age in years at baseline.

y1

Number of seizures at year one follow-up.

y2

Number of seizures at year two follow-up.

y3

Number of seizures at year three follow-up.

y4

Number of seizures at year four follow-up.

Source

Thall, PF and Vail, SC (1990) Some covariance models for longitudinal count data with over-dispersion. Biometrics, 46: 657-671.

Stukel, TA (1993) Comparison of methods for the analysis of longitudinal data. Statistics Med 12: 1339-1351.

Shoukri, MM and Chaudhary, MA (2007) Analysis of correlated data with SAS and R. Third Edition. Chapman & Hall/CRC.

Examples

data(Thall)

c1 <- cbind(Thall[, c(1:5)], count = Thall$y1)[, c(1:4, 6)]
c2 <- cbind(Thall[, c(1:4, 6)], count = Thall$y2)[, c(1:4, 6)]
c3 <- cbind(Thall[, c(1:4, 7)], count = Thall$y3)[, c(1:4, 6)]
c4 <- cbind(Thall[, c(1:4, 8)], count = Thall$y3)[, c(1:4, 6)]
epilepsy <- rbind(c1, c2, c3, c4)

require(lme4, quietly = TRUE)
model_glmer <- glmer(count ~ treat + base + I(age - mean(age, na.rm = TRUE)) +
  (1 | id), data = epilepsy, family = poisson)
glm_coef(model_glmer, labels = c(
  "Treatment (Prograbide/Control)",
  "Baseline count", "Age (years)"
))

pubh documentation built on Nov. 14, 2023, 1:08 a.m.