Specification
- Fits the mover-stayer model, conventional logistic, logistic-normal
and logistic-normal with end-points models to binary data.
- Fits the ordered probit and logit random
effect response models.
- Fits conventional log-linear, log-linear normal and log-linear normal
with end-point models to count data.
- Substantial control is available over the parameters of the algorithm
for the sophisticated user.
- Can deal with very long sequences of data.
- Can deal with multi-process data, where each response sequence is of a
different type, currently limited to the simultaneous analysis of
trivariate correlated sequences.
- Comprehensive online user manual.
and online training materials.
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Applications
- Studies of voting behaviour, trade union membership, economic activity
and migration.
- Demographic surveys.
- Studies of infertility in humans.
- Animal husbandry.
- Absenteeism studies.
- Clustered sampling schemes.
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