The SURVEYLOGISTIC Procedure |
Determining Observations for Likelihood Contributions
If you use the events/trials syntax, each observation is split into two observations. One has the response value 1 with a frequency equal to the frequency of the original observation (which is 1 if the FREQ statement is not used) times the value of the events variable. The other observation has the response value 2 and a frequency equal to the frequency of the original observation times the value of (trials
events). These two observations have the same explanatory variable values and the same FREQ and WEIGHT values as the original observation.
For either the single-trial or the events/trials syntax, let
index all observations. In other words, for the single-trial syntax,
indexes the actual observations. And, for the events/trials syntax,
indexes the observations after splitting (as described previously). If your data set has 30 observations and you use the single-trial syntax,
has values from 1 to 30; if you use the events/trials syntax,
has values from 1 to 60.
Suppose the response variable in a cumulative response model can take on the ordered values
, where
is an integer
. The likelihood for the
th observation with ordered response value
and explanatory variables vector ( row vectors)
is given by
where
is the logistic, normal, or extreme-value distribution function;
are ordered intercept parameters; and
is the slope parameter vector.
For the generalized logit model, letting the
st level be the reference level, the intercepts
are unordered and the slope vector
varies with each logit. The likelihood for the
th observation with ordered response value
and explanatory variables vector
(row vectors) is given by