___________________________________________________________________
 |                                                                 |
 |                            PRED RES WRES                        |
 |_________________________________________________________________|
 MEANING: PRED, RES, WRES
 CONTEXT: NONMEM output

 DISCUSSION:
 NONMEM tables usually include special items: prediction, residual, and
 weighted  residual, which are generated by NONMEM.  The default labels
 for these items are PRED, RES, and WRES, respectively. Synonyms may be
 specified  on the $TABLE record for one or more of these labels.  With
 the NOAPPEND option on this record, the three items are  not  included
 in a table
 unless explicity listed on the $TABLE record.                           |
 With the use of the user-routine SPTWO, the values of the RES and WRES
 items can be defined differently from the values described below.
 (See sptwo).

 These items may also be displayed in scatterplots.   Synonyms  may  be
 specified  on  the  $SCATTERPLOT record as well; synonyms specified on
 either the $TABLE or $SCATTERPLOT  record  also  apply  to  the  other
 record.

 PRED
      Prediction items are the predictions computed by the PRED subrou-
      tine.   For  population data, prediction items are always popula-
      tion predictions, i.e., they are computed at the  mean  value  of
      eta (0).

 RES
      The residual is defined as DV - PRED; that is, the observed value
      minus the prediction item.

 WRES
      The weighted residuals for an individual are formed by transform-
      ing  the individual's residuals so that under the model, assuming
      the true values of the parameters are given by the  estimates  of
      those  parameters, all weighted residuals have mean 0, unit vari-
      ance and are uncorrelated. For population data, the "weights" are
      computed at eta = 0.

 For odd-type data, the prediction items are likelihoods  (for  popula-
 tion  data, using the estimated values of the parameters, and computed
 at eta = 0).  These may not be of much interest.   The  RES  and  WRES
 items are 0.

 With a mixture model, each individual is classified into  one  of  the
 subpopulations  of the mixture according to a computation based on the
 individual's data and on the final parameter estimates.   For  a  data
 record  from  the  individual  record,  the  prediction, residual, and
 weighted residual items in the corresponding row of a table (or  point
 on a scatterplot) are based on the submodel defining the subpopulation
 into which the individual is classified.

 If the Marginal data item (MRG_) is 1 or 2 for a  given  data  record,
 then PRED is an expected prediction, rather than the prediction at the
 mean value of eta.  When the Raw-data data item (RAW_) is 1,  then  DV
 is  a raw-data average and RES is the difference between the PRED item
 and this average.
 (See displayed PRED-defined items).

REFERENCES: Guide I Section C.3.5.3, C.3.5.4
REFERENCES: Guide IV Section III.B.16, III.B.17
REFERENCES: Guide V Section 9.5, 10.7, 11.4.4.2


  
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