+--------------------------------------------------------------------+ | | | 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, 11.4.4.2Go to main index.Created by nmhelp2html v. 1.0 written by Niclas Jonsson (Modified by AJB 5/2006,11/2007,10/2012)