DROP directive

Drops terms from a linear, generalized linear, generalized additive or nonlinear model.

Options

PRINT = string tokens	What to print (model, deviance, summary, estimates, correlations, fittedvalues, accumulated, monitoring, confidence); default mode, summ, esti
NONLINEAR = string token	How to treat nonlinear parameters between groups (common, separate, unchanged); default unch
CONSTANT = string token	How to treat the constant (estimate, omit, unchanged, ignore); default unch
FACTORIAL = scalar	Limit for expansion of model terms; default * i.e. that in previous TERMS statement
POOL = string token	Whether to pool ss in accumulated summary between all terms fitted in a linear model (yes, no); default no
DENOMINATOR = string token	Whether to base ratios in accumulated summary on rms from model with smallest residual ss or smallest residual ms (ss, ms); default ss
NOMESSAGE = string tokens	Which warning messages to suppress (dispersion, leverage, residual, aliasing, marginality, df, inflation); default *
FPROBABILITY = string token	Printing of probabilities for variance and deviance ratios (yes, no); default no
TPROBABILITY = string token	Printing of probabilities for t-statistics (yes, no); default no
SELECTION = string tokens	Statistics to be displayed in the summary of analysis produced by PRINT=summary, seobservations is relevant only for a Normally distributed response, and %cv only for a gamma-distributed response (%variance, %ss, adjustedr2, r2, seobservations, dispersion, %cv, %meandeviance, %deviance, aic, bic, sic); default %var, seob if DIST=normal, %cv if DIST=gamma, and disp for other distributions
PROBABILITY = scalar	Probability level for confidence intervals for parameter estimates; default 0.95
AOVDESCRIPTION = text	Description for line in accumulated analysis of variance (or deviance) table when POOL=yes

Parameter

formula	List of explanatory variates and factors, or model formula

Description

DROP deletes terms from 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 DROP, 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 DROP 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 DROP are the same as those of the FIT directive, but with the extra NONLINEAR option which is relevant when fitting curves. For example, if we have a variate Dilution and a factor Solution, the program below will fit curves with separate linear and nonlinear parameters for the different solutions.

MODEL Density

TERMS Dilution * Solution

FITCURVE [PRINT=model,estimates; CURVE=logistic;\

  NONLINEAR=separate] Dilution * Solution

If we then put

DROP [NONLINEAR=common]

the curves will be constrained to have common nonlinear parameters, but all linear parameters will still be estimated separately for each group.

Options: PRINT, NONLINEAR, CONSTANT, FACTORIAL, POOL, DENOMINATOR, NOMESSAGE, FPROBABILITY, TPROBABILITY, SELECTION, PROBABILITY, AOVDESCRIPTION.

Parameter: unnamed.

See also

Directives: MODEL, TERMS, FIT, FITCURVE, FITNONLINEAR, ADD, SWITCH, TRY.

Functions: COMPARISON, POL, REG, LOESS, SSPLINE.

Commands for: Regression analysis.

Example

" Example FIT-3: Comparing linear regressions between groups
 
  Experiments on cauliflowers in 1957 and 1958 provided data on
  the mean number of florets in the plant and the temperature during
  the growing season (expressed as accumulated temperature above 0 deg C."

" The counts and temperatures are in a file called 'FIT-3.DAT'"
FILEREAD [NAME='%gendir%/examples/FIT-3.DAT'] MnCount,AccTemp
" The first 7 values are from 1957 and the rest from 1958;
  set up a factor to distinguish the two years."
FACTOR [LEVELS=!(1957,1958); VALUES=7(1957,1958)] Year

" Fit a linear regression model of the mean count of florets on
  accumulated temperature - first ignoring the division into two years."
MODEL MnCount
TERMS AccTemp*Year
FIT AccTemp

" Fit parallel regressions for the two years."
ADD Year

" Fit separate regressions for the two years."
ADD AccTemp.Year

" Display the accumulated summary: an analysis of parallelism."
RDISPLAY [PRINT=accumulated]

" Show the parallel models."
DROP [PRINT=*] AccTemp.Year
RGRAPH [GRAPHICS=high]

" Extract the parameter estimates and s.e.s
  and display the common slope and its s.e."
RKEEP ESTIMATES=Esti; SE=Se
CALC Slope,SlopeSE = (Esti,Se)$[2]
PRINT Slope,SlopeSE