What is null hypothesis for PROC GLM? what is estimate, P, and T value in the model output?

[captainprice0]

After running proc GLM with multiple regressors.

I got the regressors and their Estimate, P, and T values.

I want to find out the best regressors for my model.

how should I use P, T, or Estimate column to determine which regressors are best for my model.

Also, what is the meaning of Estimate, P, and T values in model output.

Please help

this is how the output looks like

Dependent	Parameter	Estimate	Biased	StdErr	tValue	Probt
ln_dep1	ln_rw_base*region_nm PACIFIC NORTHWEST	0.9604395696	0	0.00481642	199.41	0.0000
ln_dep1	ln_rw_base*region_nm PACIFIC CENTRAL	0.9601801559	0	0.00476460	201.52	0.0000
ln_dep1	ln_rw_base*region_nm NEW ENGLAND	0.9600740196	0	0.00479192	200.35	0.0000
ln_dep1	ln_rw_base*region_nm PACIFIC NORTH	0.9600171774	0	0.00475982	201.69	0.0000

[PeterClemmensen]

This sounds like multiple questions regarding understanding the GLM output.

I recommend that you take a look at some of the vell described PROC GLM examples from the documentation here:

https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_glm_sect001...

[Ksharp]

P-Value is more small , the variable is more significant .

Also Check  PROC GLMSELECT + SELECTION=LASSO 

[ballardw]

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@Ksharp wrote:

P-Value is more small , the variable is more significant .

Also Check  PROC GLMSELECT + SELECTION=LASSO 

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My $0.02 Philosophical difference on p-value interpretaton: The p-value is used to reject the Null hypothesis or not. The rejection level should be specified before the test is done.

With that caveat small values such as 0.05 or 0.025 are common values to compare and a p-value smaller than those will reject the null hypothesis.

[PaigeMiller]

Agreeing with @PeterClemmensen, your questions are all basic statistics, that can be found in documentation provided by SAS and in many statistics textbooks, and you need to do some reading there to learn these fundamental concepts.