How do I interpret PROC GLIMMIX- Standard Errors that are all similar?

[JAO1]

I am using PROC GLIMMIX to analyse a continuous response variable that is dependent on 4 independent categorical variables..

Each of the 4 independent variables has two levels. 

The first independent categorical variable is a soil type (soilA, soilB)

The second independent categorical variable is a plant type (strawberry, raspberry)

The third independent categorical variable is a color type (blue, red)

The fourth is a light type (IR, NIR)

The response variable  is the plant fluorescence. 

My syntax looks like this:

proc glimmix;
class soil color plant light;
model FL = plant soil / solution;
random intercept / subject=light;
lsmeans plant / cl ilink;
run;

The results that I get do not look right.

What I am obtaining are values of my standard error that are all similar.

Kindly assist me.

[PaigeMiller]

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@JAO1 wrote:

The results that I get do not look right.

What I am obtaining are values of my standard error that are all similar.

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Could you please show us the results?

Could you explain why similar standard errors seems to be a problem?

[JAO1]

Based on the examples in the GLIMMIX procedure, standard errors are
dissimiliar, yet all of the ones that I have calculated for my treatment
groups are the same.

[PaigeMiller]

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@JAO1 wrote:
Based on the examples in the GLIMMIX procedure, standard errors are dissimiliar, yet all of the ones that I have calculated for my treatment groups are the same.

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I'm afraid this doesn't convince me.

[JAO1]

The results in this example from the GLIMMIX Procedure as well as other examples always result in dissimilar Standard Errors. 

What am I doing wrong?

[PaigeMiller]

Please show us YOUR results