Calculating Slopes and Slope difference for a categorical-continuous-continuous categorical variable

joannahh — Mon, 20 May 2019 08:16:00 GMT

Hello,

Using an ecological assessment design (where people report their negative affect and social interaction every three hours each day across 5 days of the week), I am trying to calculate's participants' hourly experience of Negative Affect (NA) when interacting with family members compared to No interaction (FamilyInteraction: categorical var).

I am trying to see how trait levels of neuroticism and extraversion may further explain this relationship so I am using a three-way interaction with a dichotomous variable (FamilyInteraction) and two continuous variables (neuroticism and extraversion).

So far, the only way I have figured out a way to calculate the simple slopes and slope contrast is by using proc plm and using the lsmestimate command. But in order to use this syntax, I have to make one of the personality vars into a categorical variable. If I want to keep both of my personality variables as continuous variables, what syntax code can I use?

*Below purpose syntax is the main model of the analysis

proc mixed noclprint covtest ;
class ID FamilyInteraction;
model NA= FamilyInteraction|Neuro|Extraversion/ solution ddfm = bw;
RANDOM intercept / SUBJECT=Day;
RANDOM intercept / SUBJECT=ID(Hour);
store Save;run;

proc plm noclprint restore=Alonea;
effectplot interaction (x=FamilyInteractionsliceby=Neuro) / at(Extra=1.0741531 1.9140935) clm connect;
run;

*Below syntax in blue the way I would calculate the slopes & slope differences if one of the personality traits (Neuro) is made into a categorical variable and used in the proc plm lsmestimate command.

proc plm noclprint restore=Alonea;
lsmestimate C1r*LonelyCat 'No Fam-Yes Fam, Low Neuro, Extra=Low' [1, 1 1] [-1, 2 1],
'No Fam-Yes Fam, High Neuro, Extra=Low' [1, 1 2] [-1, 2 2] / e adj=bon at Extra=1.0741531;

lsmestimate C1r*LonelyCat 'No Fam-Yes Fam, Low Neuro, Extra=High' [1, 1 1] [-1, 2 1],
'No Fam-Yes Fam, High Neuro, Extra=High' [1, 1 2] [-1, 2 2] / e adj=bon at Extra=1.9140935; run;

proc plm noclprint restore=Alonea;
lsmestimate FamilyInteraction*Neuro' diff No Fam-Yes Fam, LowNeuro- HighNeuro, Extra=Low' [1, 1 1] [-1, 2 1] [-1, 1 2] [1, 2 2] / e at Extra=1.0741531 joint;
lsmestimate FamilyInteraction*Neuro' diff No Fam-Yes Fam, LowNeuro- HighNeuro, Extra=High' [1, 1 1] [-1, 2 1] [-1, 1 2] [1, 2 2] / e at Extra=1.9140935 joint;
run;

I really appreciate any help I can get and please let me know if I can further clarify anything!

Re: Calculating Slopes and Slope difference for a categorical-continuous-continuous categorical vari

PaigeMiller — Mon, 20 May 2019 11:21:27 GMT

The SOLUTION option in MODEL statement of PROC MIXED will provide the slopes.

topic Re: Calculating Slopes and Slope difference for a categorical-continuous-continuous categorical vari in New SAS User

Calculating Slopes and Slope difference for a categorical-continuous-continuous categorical variable

Re: Calculating Slopes and Slope difference for a categorical-continuous-continuous categorical vari