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Three-Way Interaction -- Significant Differences in Slopes

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Three-Way Interaction -- Significant Differences in Slopes

Hi everyone,

I'm running a multilevel model with proc mixed. I'm trying to estimate a three way interaction between homophobia (called zhomodiff), rater gender (called gender), and stimulus gender in predicting a stimuli's attractiveness (while controlling for the other things in the model: e.g. group, SCAT, PCAT).

I found a three way interaction between homophobia, rater gender, and stimulus. I was able to graph it by obtaining estimates through the LSMEANS statements. However, since the level of homophobia is a continuous variable, I am unsure if I will be able to contrast the differences in slopes based on the level of homophobia.

Here's my code thus far:

PROC MIXED covtest data=data;

CLASS id Stimulus_Number group gender sgend SCat PCat  age race relationship_status;

MODEL  Attractiveness = zhomodiff | gender | sgend group SCat | PCat | Sgend /solution DDFM=SATTERTH;

REPEATED Stimulus_Number /SUBJECT=id TYPE=cs;

LSMEANS Gender*SGEND/ AT zhomodiff = 1 pdiff;

LSMEANS Gender*SGEND/ AT zhomodiff= 0 pdiff;

LSMEANS Gender*SGEND/ AT zhomodiff= -1 pdiff;

run;

Is there anyway to contrast the significance between two slopes? Is there any way to examine the statistical difference between two slopes?

Thanks!

Nick

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