Description Usage Arguments Details Value Author(s)
Fit a log-linear model. This is a wrapper function for our own variant of
the glm
function, pirls
.
1 | flat.log.linear(pop, model.terms, rasch = FALSE)
|
pop |
The CRC data as a data frame. |
model.terms |
The columns of the standard design matrix to include in the model. For example, "c1", "c2" for main effects, and "c12" for interactions. |
rasch |
Logical: Is this the Rasch model? |
Maximum likelihood estimation is used, conditioning on the observed population as if it were the full population.
A vector of log-linear coefficients. The first coefficient is the
intercept, and the rest correspond (in order) with the model.terms
argument
Zach Kurtz
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