Consider a dataset consisting of 610 males involved in a study of coronary heart disease. The outcome variable is CHD status (1 = case, 0 = non case), the exposure variable of interest is CAT which is a dichotomous variable that indicates high (coded 1) or normal (coded 0) catecholamine level. The only other variables recorded in the data set are AGE (1 = age > 55, 0 = age ≤ 55) and ECG (1 = abnormal, 0 = normal). The dataset involving the above variables is given as follows: data data1; input cases total CAT AGE ECG; cards; 17 275 0 0 0 15 121 0 1 0 7 59 0 0 1 5 32 0 1 1 1 8 1 0 0 10 40 1 1 0 4 17 1 0 1 14 58 1 1 1 ; run; We are interested in the following logistic model: As given in the SAS code above, the model is a full model with all main effects and interactions (both two way and three way interactions). A main effect model can be obtained from SAS by this model statement – model cases/total = AGE CAT ECG / cl; Perform a hypothesis test to see if the interactions (including all of the two-way and the three-way Interactions) help with the model using a likelihood ratio test (LRT) to compare the full model and the main effect model using alpha of 0.05.
Consider a dataset consisting of 610 males involved in a study of coronary heart disease. The outcome variable is CHD status (1 = case, 0 = non case), the exposure variable of interest is CAT which is a dichotomous variable that indicates high (coded 1) or normal (coded 0) catecholamine level. The only other variables recorded in the data set are AGE (1 = age > 55, 0 = age ≤ 55) and ECG (1 = abnormal, 0 = normal). The dataset involving the above variables is given as follows:
data data1;
input cases total CAT AGE ECG;
cards;
17 275 0 0 0
15 121 0 1 0
7 59 0 0 1
5 32 0 1 1
1 8 1 0 0
10 40 1 1 0
4 17 1 0 1
14 58 1 1 1
;
run;
We are interested in the following logistic model:
As given in the SAS code above, the model is a full model with all main effects and interactions (both two way and three way interactions). A main effect model can be obtained from SAS by this model statement –
model cases/total = AGE CAT ECG / cl;
Perform a hypothesis test to see if the interactions (including all of the two-way and the three-way Interactions) help with the model using a likelihood ratio test (LRT) to compare the full model and the main effect model using alpha of 0.05.
Trending now
This is a popular solution!
Step by step
Solved in 5 steps with 22 images
