Two-way ANOVA with and without interaction

[SASstudent2013]

Hello, I need to perform 2-way ANOVA with and without interaction. I am wondering if the code below is correct? Variable 'sex' can be a 1 or 2, variable 'agegrp' can be a 1, 2, or 3, and variable peri is a continuous variable that is a measurement. I need to interpret the coefficient for sex in the one without interaction, and then determine whether agegrp is an effect modifier.  Code and output are below. Any and all advice is appreciated!! I'm not sure if I have this setup correctly or not.

CODE:

/*Two way ANOVA by age group and sex with no interaction term. Save the predicted values into a data set called out1*/

proc glm data=bone;

class sex agegrp;

model peri = sex agegrp;

output out=out1;

run;

proc print data=out1;

run;

/*Two way ANOVA by age group and sex with interaction. Save the predicted values into a data set called out2*/

proc glm data=bone;

class sex agegrp;

model peri = sex agegrp sex*agegrp;

estimate 'gender: age group = < 12' sex 1 -1 agegrp*sex 1 0 0 -1 0 0;

estimate 'gender: age group = between 12 and 20' sex 1 -1 agegrp*sex 0 1 0 0 -1 0;

estimate 'gender: age group = 20 and older' sex 1 -1 agegrp*sex 0 0 1 0 0 -1;

output out=out2;

run;

OUTPUT -without interaction:

The GLM Procedure

Dependent Variable: peri

        

Model	3	38215.08431	12738.36144	311.43	<.0001
Error	661	27036.95555	40.90311
Corrected Total	664	65252.03987

     

0.585653

10.10223

6.395554

63.30836

        

sex	1	2846.67657	2846.67657	69.60	<.0001
agegrp	2	35368.40774	17684.20387	432.34	<.0001

        

sex	1	2377.64138	2377.64138	58.13	<.0001
agegrp	2	35368.40774	17684.20387	432.34	<.0001

OUTPUT - with interaction:

Dependent Variable: peri

        

Model	5	39885.94536	7977.18907	207.24	<.0001
Error	659	25366.09451	38.49180
Corrected Total	664	65252.03987

     

0.611260

9.799932

6.204176

63.30836

        

sex	1	2846.67657	2846.67657	73.96	<.0001
agegrp	2	35368.40774	17684.20387	459.43	<.0001
sex*agegrp	2	1670.86105	835.43052	21.70	<.0001

        

sex	1	3354.12307	3354.12307	87.14	<.0001
agegrp	2	36322.30089	18161.15045	471.82	<.0001
sex*agegrp	2	1670.86105	835.43052	21.70	<.0001

       

gender: age group = < 12	0.56899907	0.70119138	0.81	0.4174
gender: age group = between 12 and 20	5.88697422	0.79962957	7.36	<.0001
gender: age group = 20 and older	8.49302897	1.19728344	7.09	<.0001

[PGStats]

Hi. What is the intended purpose of your ESTIMATE statements? - PG

[PaigeMiller]

I need to interpret the coefficient for sex in the one without interaction, and then determine whether agegrp is an effect modifier.

You don't ask SAS to compute the coefficients. You can't interpret them unless you have SAS compute them.

Also, I am not familiar with the phrase "effect modifier". Does that mean "interaction is statistically significant"?