topic Re: Proc glimmix for split plot with three independent variables in Statistical Procedures

Proc glimmix for split plot with three independent variables

ValeriaRodz — Thu, 25 Jan 2018 02:01:11 GMT

Hi everyone! First of all sorry for my English, is not my first language and there's probably a lot misspelled words ahead. I'm also new to SAS and I'm trying to run my code for the first time. It's a split plot statistical model where the whole plot is a bull where I analyze "sexo" x "edad" and the split plot is the muscle in which I analyze the type of muscle. I tried this code:

Proc glimmix data= castradocruza;
Class edad musc sexo toro;
Model tern_co = Edad | Musc | sexo;
Random toro(edad);
Lsmeans edad Edad | Musc | sexo / pdiff lines;
Run;

When I run the code it ends up in the result tab with an invalid data error (picture in the attachment). I've checked all my raw data and so far haven't found an error. Could it be that the code doesn't work for this type of statistical model?

Thanks.

Re: Proc glimmix for split plot with three independent variables

sld — Thu, 01 Feb 2018 03:23:38 GMT

Based on the output you posted, only 6 observations are in your dataset. Your model is a 6 x 6 x 6 factorial in 6 blocks. You cannot fit this model with only 6 observations.

You will need either more than 6 observations or a different model. The Community will need more information to provide more help. Please post your SAS code and your dataset (or an example of your dataset).

Re: Proc glimmix for split plot with three independent variables

ValeriaRodz — Thu, 01 Feb 2018 14:57:54 GMT

Hi! My raw data was corrupted and only a few observations were showing. I fixed this importing the raw data instead of copy+pasting all of it.

/** Import an XLSX file. **/

PROC IMPORT DATAFILE="/folders/myshortcuts/SASUniversityEdition/Myfolders/word.xlsx"

OUT=WORK.MYEXCEL

DBMS=XLSX

REPLACE;

RUN;

/** Print the results. **/

PROC PRINT DATA=WORK.MYEXCEL; RUN;

In regards to the model, I believe its a 2 x 2 x 3 (sex: castrated and intact, muscles: LD, LM and age groups: group 1, 2 and 3). Even though I fixed the problem with the corrupted raw data my code is not working. Probably I'm not using the right one. This is the whole code I was using before I imported the raw data:

data cruza;

input edad $ musc $ sexo $ toro tern_co Col_L Col_a Col_b pH;

datalines;

1 LD i 1 4.9 29.33 20.27 17.91 5.6
1 LM i 1 3.3 44.92 15.46 17.8 5.13
1 LD i 2 2.6 33.22 18.53 17.29 5.55
1 LM i 2 3.6 44.38 14.74 17.66 5.53
1 LD i 3 5.2 38.74 17.49 15.4 5.47
1 LM i 3 3.9 47.97 12.14 14.44 5.51
1 LD i 4 4.5 36.49 15.43 12.05 5.49
1 LM i 4 4.1 44.86 14.32 14.64 5.43
1 LD c 5 4 28.47 19.34 17.22 5.64
1 LM c 5 3.6 47.9 13.02 17.87 5.48
1 LD c 6 3.9 29.57 20.11 16.55 5.49
1 LM c 6 4.4 42.41 16.1 17.13 5.38
1 LD c 7 6.4 33.67 13.82 10.52 5.66
1 LM c 7 3.5 51.67 11.48 15.29 5.62
2 LD i 1 7.4 35.84 21.48 19.73 5.52
2 LM i 1 3.1 42.18 15.83 18.07 5.66
2 LD i 2 4.7 32.12 16.24 11.5 5.54
2 LM i 2 3.5 39.48 15.74 13.24 5.8
2 LD i 3 1.6 27.52 12.71 8.3 5.57
2 LM i 3 2.2 32.95 12.72 9.92 5.29
2 LD i 4 6.6 31.88 18.85 12.78 5.47
2 LM i 4 1.7 43.81 12.96 13.28 6.26
2 LD i 5 4.2 33.35 15.53 11.08 5.94
2 LM i 5 3.7 44.54 12.78 13.52 5.93
2 LD c 6 4 32.35 21.36 19.52 5.51
2 LM c 6 2.8 41.68 17.34 18.9 5.42
2 LD c 7 2.8 34.4 15.96 11.63 5.42
2 LM c 7 3 43.85 15.23 14.98 5.43
2 LD c 8 4.2 37.96 15.01 11.91 5.61
2 LM c 8 2.4 48.28 13.37 15.36 5.58
3 LD i 1 9.6 30.95 15.13 11.43 5.92
3 LM i 1 4.4 37.87 14.27 12.79 5.75
3 LD i 2 6.5 33.78 18.41 13.29 6.78
3 LM i 2 5.2 41.18 16.67 14.65 5.89
3 LD i 3 5.8 32.89 16.03 11.48 5.87
3 LM i 3 8.5 46.38 15.79 15.71 5.85
3 LD i 4 5.9 30.26 15.53 10.17 5.95
3 LM i 4 6.6 36.56 14.05 11.12 5.89
3 LD i 5 4.5 36.49 15.43 12.05 5.49
3 LM i 5 4.1 44.86 14.32 14.64 5.43
3 LD i 6 7.4 35.84 21.48 19.73 5.52
3 LM i 6 3.1 42.18 15.83 18.07 5.66
3 LD i 7 9.7 31.73 14.19 10.61 5.86
3 LM i 7 4.4 38.97 19.47 16.52 5.8
3 LD c 8 3.8 33.16 15.43 11.33 5.97
3 LM c 8 5 42.88 16.69 15.5 5.8
3 LD c 9 5 34.05 16.38 11.67 5.94
3 LM c 9 4.5 45.51 16.17 15.48 5.84
3 LD c 10 7.7 33.44 17.43 12.74 5.96

;

Run;

proc glimmix data=cruza;

class edad musc sexo toro;

model pH = sexo | musc;

random toro(edad);