+--------------------------------------------------------------------+
| |
| MDVRES |
| |
+--------------------------------------------------------------------+
MEANING: NONMEM-PRED global variables
CONTEXT: PRED routine
USAGE:
USE NMPRD_INT, ONLY: MDVRES
GLOBAL DECLARATION:
INTEGER(KIND=ISIZE) :: MDVRES
DISCUSSION:
MDVRES stands for missing dependent variable (MDV) for residual (RES).
Setting MDVRES to 1 is equivalent to temporarily declaring an observa-
tion as missing during the computation of residuals and weighted
residuals.
MDVRES=0 (default)
Set MDVRES to 1 in the $ERROR or $PRED routine if you do not want to
include a particular observation in the computation of residual and
weighted residuals.
One situation in which this may be useful is when F_FLAG is used
because some observations are predictions (F_FLAG=0) and others are
likelihood or -2 log likelihood values (F_FLAG=1 or F_FLAG=2). By
default, if F_FLAG is set to 1 or 2 for any observation within an
individual record, the RES and WRES items will be 0 for all data
records in the individual record. When MDVRES is set to 1 for any
observation, this overrides the default. NONMEM will compute RES and
WRES for all observations for which MDVRES is set to 0. MDVRES should
be set to 1 with all observations having F_FLAG=1 or F_FLAG=2, but may
be set to 1 for other observations as well.
EXAMPLE:
Supose that some observations are assessed by a non-normal distribu-
tion likelihood such as the PHI() function for below detection limit
values, in which F_FLAG is set. By setting MDVRES=1 to these particu-
lar below detection values, the weighted residual algorithm can assess
the remaining normally distributed values for that subject.
$ERROR
SD = THETA(5)
IPRED = LOG(F)
DUM = (LOQ - IPRED) / SD
CUMD = PHI(DUM)
IF (TYPE .EQ. 1) THEN
F_FLAG = 0
Y = IPRED + SD * ERR(1)
ENDIF
IF (TYPE .EQ. 2) THEN
F_FLAG = 1
Y = CUMD
MDVRES=1
ENDIF
REFERENCES: Guide Introduction_7
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