- RANDOM random-effects distribution SUBJECT=variable <options> ;
The RANDOM statement defines the random effects and their
distribution. The random effects must be represented by symbols
that appear in your SAS programming statements. They typically
influence the mean value of the distribution specified in the MODEL
statement. The RANDOM statement consists of a list of the random
effects (usually just one or two symbols), a tilde
, the distribution for the random
effects, and then a SUBJECT= variable.
NOTE: The input data set must be clustered according to the
SUBJECT= variable. One easy way to accomplish this is to sort your
data by the SUBJECT= variable prior to calling PROC NLMIXED. PROC
NLMIXED does not sort the input data set for you; rather, it
processes the data sequentially and considers an observation to
be from a new subject whenever the value of its SUBJECT= changes
from the previous observation.
The only distribution currently available for the random effects is
with mean m and variance v.
This syntax is
illustrated as follows for one effect:
random u ~ normal(0,s2u) subject=clinic;
For multiple effects, you should specify bracketed vectors for m
and v, the latter consisting of the lower triangle of the
random-effects variance matrix. This is illustrated for two random
effects as follows.
random b1 b2 ~ normal([0,0],[s2b1,cb12,s2b2]) subject=person;
The SUBJECT= variable determines when new realizations of the random
effects are assumed to occur. PROC NLMIXED assumes that a new
realization occurs whenever the SUBJECT= variable changes from the
previous observation, so your input data set should be clustered
according to this variable. One easy way to accomplish this is to
run PROC SORT prior to calling PROC NLMIXED using the SUBJECT=
variable as the BY variable.
Only one RANDOM statement is permitted, so multilevel nonlinear
mixed models are not currently accommodated.
The following options are available in the RANDOM statement:
specifies the alpha level to be used in computing t statistics
and intervals. The default value corresponds to the ALPHA= option in
the PROC NLMIXED statement.
specifies the degrees of freedom to be used in computing t
statistics and intervals in the OUT= data set. The default value
corresponds to the DF= option in the PROC NLMIXED statement.
requests an output data set
containing empirical Bayes estimates of the random effects
and their approximate standard errors of prediction.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.