ADD directive
Adds extra terms to a linear, generalized linear, generalized additive or nonlinear model.
Options
Parameter
Description
ADD adds terms to the current regression model, which may be linear, generalized linear, generalized additive, standard curve or nonlinear. It is best to give a TERMS statement before investigating sequences of models using ADD, in order to define a common set of units for the models that are to be explored. If no model has been fitted since the TERMS statement, the current model is taken to be the null model.
The model fitted by ADD will include a constant term if the previous model included one, and will not include one if the previous model did not. You can, however, change this using the CONSTANT option.
The options of ADD are almost all the same as those of the FIT directive, and are described there. There is also an extra option NONLINEAR. This is relevant when fitting curves. For example, if we have a variate Dilution and a factor Solution, the program below will fit parallel curves for the different solutions.
MODEL Density
TERMS Dilution * Solution
FITCURVE [PRINT=model,estimates; CURVE=logistic] \
Dilution + Solution
If we then put
ADD Dilution.Solution
the curves are still constrained to have common nonlinear parameters, but all linear parameters are estimated separately for each group. Alternatively, if we put
ADD [NONLINEAR=separate] Dilution.Solution
different nonlinear parameters will be estimated for each solution too; so only the information about variability is pooled.
Options: PRINT, NONLINEAR, CONSTANT, FACTORIAL, POOL, DENOMINATOR, NOMESSAGE, FPROBABILITY, TPROBABILITY, SELECTION,
Parameter: unnamed.
Action with
RESTRICT
If a TERMS statement was given before fitting the model, any restrictions on the variates or factors in the model will have been implemented then. So any restrictions on vectors involved in the model specified by ADD will be ignored. If no TERMS statement has been given and ADD introduces new terms into the model, restrictions on the variates or factors in these terms will be taken into account and may cause the units involved in the regression to be redefined.