| muscatine {bild} | R Documentation |
Muscatine
Description
This example is a subset of data from the Muscatine Coronary Risk Factor Study, a longitudinal study of coronary risk factors in school children from Muscatine (Iowa, USA).
Usage
data(muscatine)
Format
A data frame with 156 observations on the following 7 variables.
ididentifies de number of the individual profile. This vector contains observation of 52 individuals.
obesea numeric vector that identify the obesity status (1="yes", 0="no") of a child at each occasion.
sexa factor with levels
1for "female" and0for "male".timea numeric vector (1,2,3) indicating the observed time points.
countsa numeric vector indicating the number of times that each profile is replicated.
Details
The data set presented by Fitzmaurice, Laird and Lipsitz (1994) contains records on 1014 children who were 7-9 years old in 1977 and were examined in 1977, 1979 and 1981. Height and weight were measured in each survey year, and those with relative weight greater than 110 The binary response of interest is whether the child is obese (1) or not (0). However, many data records are incomplete, since not all children participate in all the surveys. This data set was also analyzed by Azzalini (1994).
Source
Fitzmaurice, G. M., Laird, N. M. and Lipsitz, S. R. (1994). Analyzing incomplete longitudinal binary responses: a likelihood based approach. Biometrics, 38, 602-612.
References
Azzalini, A. (1994). Logistic regression for autocorrelated data with application to repeated measures. Biometrika, 81, 767-775.
Examples
str(muscatine)
# we decompose the time effect in orthogonal components
muscatine$time1 <- c(-1, 0, 1)
muscatine$time2 <- c(1, -2, 1)
# second order Markov Chain without random effects
musc2 <- bild(obese~(time1+time2)*sex, data=muscatine,
time="time1", aggregate=sex, trace=TRUE, dependence="MC2")
summary(musc2)
getAIC(musc2)
getLogLik(musc2)
fitted(musc2)