[問題] sas mixed model data處理
我主要是想看一群人某個健康變項跟空氣污染之間的關係
手邊有這群人重複測量的資料
為了進一步分析在冷暖季的空氣污染影響
而將資料分成兩群組
兩組樣本數一樣多
可是程式碼一組可以跑一組出現了以下的警告而無法跑出結果
WARNING: Stopped because of too many likelihood evaluations.
WARNING: Did not converge.
我找到別人回覆某人問題的解答
可是光從信件中我不知道要如何修改程式
想請問板上的高手有沒有人可以幫忙，謝謝
我的程式碼如下
proc mixed noclprint covtest data=zzzz ic;
class smoking gender ht dm medica;
model a=CO age bmi2 smoking gender ht dm medica tem rh /s ddfm=betwithin cl;
repeated / subject=num type=un rcorr r;
run;
信件連結
http://www.listserv.uga.edu/cgi-bin/wa?A2=ind0207a&L=sas-l&P=17502
主要內文如下
There are any number of different approaches which you might use
to address your problem. First, you could just change the number
of likelihood evaluations which SAS performs before stating that
convergence could not be obtained. The option MAXFUNC allows you
to specify the number of likelihood evaluations the MIXED procedure
should perform before stopping. Note that this is different from
the number of iterations which should be performed before stopping.
The number of iterations to perform is controlled by the option
MAXITER. These options are specified on the PROC MIXED invocation.
You can also change the convergence criterion. The default
convergence criterion is a Hessian convergence with tolerance 1E-8.
You can change the tolerance to something larger, or you can specify
a different convergence criterion altogether. The various criteria
are also options to the PROC MIXED statement. Rather than my
reciting the manual here, I'll let you look them up.
In addition to changing the convergence criterion and/or allowing
PROC MIXED to run longer, you can employ the PARMS statement to
evaluate the likelihood at various values for the variance and
covariance of the random effects. You can then plot the likelihood
surface as a function of the variances. This can be instructive
about problems which you might encounter in estimating the variance
and covariance terms. The PARMS statement also allows SAS to start
the iterative process from points which are potentially nearer to
the solution than the initial values of 0.
麻煩你們了，謝謝
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