Missing value (".") in the PROC MIXED output table

[ANKH1]

Hi, 

What does a "." mean in the proc mixed? I get this for the variable TRT. For some reason, it runs perfectly well when I input data for 50 subjects but when I use the same model for 30 subjects TRT is a ".". 

This is the code:

PROC MIXED DATA=MEANS30;

CLASS ID SEX AGE SES TRT BL0;
MODEL TOTAL = TRT|SEX|AGE BL0/ OUTPM=MEANS30RESIDS RESIDUAL VCIRY;
REPEATED SES/TYPE=CS SUB=ID;
LSMEANS TRT|SEX|AGE/ADJUST=TUKEY;
RUN;

Thanks!

[ballardw]

The dot is the default value that SAS uses to display any missing numeric.

you can change the character using the OPTIONS statement.

For example run:

options missing='?';

before the proc mixed.

I suspect there are other differences in your data other than the number of observations.

In some cases you may get a "missing" indicator because a statistic or parameter cannot be estimated for some reason with the specific data, model and options chosen.

Without example output, or better yet input data, the exact cause will remain a mystery.

[ANKH1]

Thank you for your response!

This is output table I get when I run proc mixed:

Type 3 Tests of Fixed Effects

Num      Den

Effect                    DF           DF           F Value             Pr > F

TRT                         4              0              3.59                    .

SEX                         1              29           12.79              0.0012

SEX*TRT                 4              0             3.33                     .

AGE                         1             29            1.01                0.3235

AGE*TRT                3              0             3.19                      .

SEX*AGE                1              29           0.02                 0.8845

SEX*AGE*TRT       2              0             1.39                      .

BL0                         131          0             16.86                    .

This is the proc mixed model

PROC MIXED DATA=MEANS32;
CLASS ID SEX AGE SES TRT BL0;
MODEL TOTAL = TRT|SEX|AGE BL0/ OUTPM=MEANS32RESIDS RESIDUAL VCIRY;
REPEATED SES/TYPE=CS SUB=ID;
LSMEANS TRT|SEX|AGE/ADJUST=TUKEY;
RUN;

We want BL0 to be a covariate. This variable is continuous. 

This is the header of the datalines:

DATA MEANS32;
INPUT ID$   SEX$   AGE$   SES$   TRT$   BL0   BL120  TOTAL  PRE  POST  MEAL;
DATALINES;

PA03 M O 3 A 75.25 79 62.85 74.94 14.50 -70.5
PB05 F O 4 A 58.25 71.25 50.88 61.66 7.75 -62.5
PS06 M O 5 A 81.25 82.25 67.60 79.63 19.50 -63.75
PR08 M O 2 A 60 86.25 60.40 72.41 12.38 -75.75
PA10 F O 1 A 59.75 95.75 62.30 76.56 5.25 -90

Weird thing is that when we used data for 50 id's it ran everything, but when we reduced that number to 30 we got the output showed above (Type 3 Tests of Fixed Effects). 

With this info, is it possible to know why is that happening?

Thanks in advance

[Rick_SAS]

Looks like the number of joint levels of TRT|SEX|AGE exceeds the number of observations, so there are not enough denominator degrees-of-freedom to perform an F test. Is age really a classification variable? AGE is a character variable with ... how many levels? Six or more?

[PaigeMiller · Accepted solution]

We want BL0 to be a covariate. This variable is continuous. 

Take BL0 out of the CLASS statement. This most likely solves the problem you are having.

[ANKH1]

It worked! Now we don't get any missing values on the type 3 effects output table. This by removing the covariate from the CLASS statement. Why is that? 

Thank you!

[PaigeMiller]

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@ANKH1 wrote:

It worked! Now we don't get any missing values on the type 3 effects output table. This by removing the covariate from the CLASS statement. Why is that?

---

If you submit the right code, where you tell SAS that a continuous variable is continuous (by not putting it in the CLASS statement), SAS does what you want.

If you tell SAS a continuous variable is a CLASS variable, which it is not, it will eat up a lot of degrees of freedom, and then many other things in your model can't be estimated because there aren't enough degrees of freedom left.

[ANKH1]

Thanks for explaining that!