Hello All R Users,
Function loglm() in library MASS can be cajoled to accomodate
structural zeros in a cross-classification table. An example from
Fienberg demonstrates how this can be done.
My question is: Can the function glm() perform the same task? Can
glm() estimate a log-linear model with fixed zeros like loglm()?
Thanks for your help,
Andrew
## Fienberg, The Analysis of Cross-Classified Contingency Tables, 2nd
ed., p.148.
## Results from survey of teenagers regarding their health concerns.
health <- data.frame(expand.grid(CONCERNS = c("sex", "menstral",
"healthy", "nothing"),
AGE = c("12-15", "16-17"),
GENDER = c("male", "female")),
COUNT = c(4, 0, 42, 57, 2, 0, 7, 20,
9, 4, 19, 71, 7, 8, 10, 21))
health <- xtabs(COUNT ~ CONCERNS + AGE + GENDER, data = health)
zeros <- data.frame(expand.grid(CONCERNS = c("sex", "menstral",
"healthy", "nothing"),
AGE = c("12-15", "16-17"),
GENDER = c("male", "female")),
COUNT = c(1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1))
zeros <- xtabs(COUNT ~ CONCERNS + AGE + GENDER, data = zeros)
library(MASS)
fm.1 <- loglm(~ CONCERNS + AGE + GENDER,
data = health, start = zeros, fitted = TRUE)
fm.1; round(fm.1$fitted, 1)
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