How to compare two or more slopes/coefficients in proc GLM?

[Davejones]

Hi Experts,

I got LT50 values under serval % relative humidity and did proc GLM analysis. How to write codes to compare slopes/coefficients among several condition groups to figure out whether there are significant differences although some groups have a significant p values?

Thanks,

Dave

[PaigeMiller]

https://support.sas.com/kb/38/384.html and then scroll down.

[sbxkoenk]

Hello,

Usage Note 24177: Comparing parameters (slopes) from a model fit to two or more groups
https://support.sas.com/kb/24/177.html

In general ...

Make use of CONTRAST or ESTIMATE statements !!

The magical ESTIMATE (and CONTRAST) statements

By Chris Daman on SAS Learning Post April 23, 2012

https://blogs.sas.com/content/sastraining/2012/04/23/the-magical-estimate-and-contrast-statements/

"Easy button" for ESTIMATE statements

By Chris Daman on SAS Learning Post April 25, 2012

https://blogs.sas.com/content/sastraining/2012/04/25/easy-button-for-estimate-statements/

ESTIMATE Statements - the final installment

By Chris Daman on SAS Learning Post May 2, 2012

https://blogs.sas.com/content/sastraining/2012/05/02/estimate-statements-the-final-installment/

How to write CONTRAST and ESTIMATE statements in SAS regression procedures?

By Rick Wicklin on The DO Loop June 6, 2016

https://blogs.sas.com/content/iml/2016/06/06/write-contrast-estimate-statements-sas-regression-proce...

Usage Note 24447: Examples of writing CONTRAST and ESTIMATE statements

https://support.sas.com/kb/24/447.html

Usage Note 67024: Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effects in interactions and splines

67024 - Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effe...

When a model contains interactions, it is often of interest to assess the effect of one of the interacting variables. When the variable of interest is categorical, and therefore is specified in the CLASS statement, this is most easily done using the LSMEANS, SLICE, or LSMESTIMATE statement. But when the variable of interest is continuous, these statements cannot be used. Two procedures, LOGISTIC and PHREG, provide statements that can estimate the effect of increasing a continuous predictor by a specified number of units. However, when the modeled response is not binomial or a time to event, these procedures are not appropriate. Nevertheless, the HAZARDRATIO statement in PROC PHREG can still be used to provide contrast coefficients that can be used in CONTRAST or ESTIMATE statements to test or estimate the effect of a continuous predictor. This can be done for a continuous predictor involved in one or more interactions and even in constructed effects such as splines. In the case of generalized linear models that don’t use the identity link, it is important to note that the estimated effect using these coefficients is not a difference in response means. For these models, an alternative and generally easier solution is provided by the Margins macro, which can estimate the required difference in means. Both of these approaches are discussed and illustrated in this note.

BR,

Koen

[Davejones]

Thanks Koen and how to code the following Fisher Z test in  SAS ?

Zr1-r2=(Z’1-Z’2)/((1/(N1-3)+ 1/(N2-3))1/2

Zcritical=±1.96

---

@sbxkoenk wrote:

Hello,

Usage Note 24177: Comparing parameters (slopes) from a model fit to two or more groups
https://support.sas.com/kb/24/177.html

In general ...

Make use of CONTRAST or ESTIMATE statements !!

The magical ESTIMATE (and CONTRAST) statements

By Chris Daman on SAS Learning Post April 23, 2012

https://blogs.sas.com/content/sastraining/2012/04/23/the-magical-estimate-and-contrast-statements/

"Easy button" for ESTIMATE statements

By Chris Daman on SAS Learning Post April 25, 2012

https://blogs.sas.com/content/sastraining/2012/04/25/easy-button-for-estimate-statements/

ESTIMATE Statements - the final installment

By Chris Daman on SAS Learning Post May 2, 2012

https://blogs.sas.com/content/sastraining/2012/05/02/estimate-statements-the-final-installment/

How to write CONTRAST and ESTIMATE statements in SAS regression procedures?

By Rick Wicklin on The DO Loop June 6, 2016

https://blogs.sas.com/content/iml/2016/06/06/write-contrast-estimate-statements-sas-regression-proce...

Usage Note 24447: Examples of writing CONTRAST and ESTIMATE statements

https://support.sas.com/kb/24/447.html

Usage Note 67024: Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effects in interactions and splines

67024 - Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effe...

When a model contains interactions, it is often of interest to assess the effect of one of the interacting variables. When the variable of interest is categorical, and therefore is specified in the CLASS statement, this is most easily done using the LSMEANS, SLICE, or LSMESTIMATE statement. But when the variable of interest is continuous, these statements cannot be used. Two procedures, LOGISTIC and PHREG, provide statements that can estimate the effect of increasing a continuous predictor by a specified number of units. However, when the modeled response is not binomial or a time to event, these procedures are not appropriate. Nevertheless, the HAZARDRATIO statement in PROC PHREG can still be used to provide contrast coefficients that can be used in CONTRAST or ESTIMATE statements to test or estimate the effect of a continuous predictor. This can be done for a continuous predictor involved in one or more interactions and even in constructed effects such as splines. In the case of generalized linear models that don’t use the identity link, it is important to note that the estimated effect using these coefficients is not a difference in response means. For these models, an alternative and generally easier solution is provided by the Margins macro, which can estimate the required difference in means. Both of these approaches are discussed and illustrated in this note.

BR,

Koen

---

[Davejones]

Example 2.3 Analysis Using Fisher’s z Transformation

The following statements request Pearson correlation statistics by using Fisher’s z transformation for the data set Fitness:

proc corr data=Fitness nosimple fisher;
   var weight oxygen runtime;
run;

found above proc corr in

https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/procstat/procstat_corr_examples03.htm

. How to add Class "female LT50 or male LT50" to proc corr to check the effect of different % relative humidity on the slopes with LT50s?