Test to compare regression lines and R^2 values

#1
Hello

I would like to compare the regression lines and coefficients between the disease and healthy groups to see if the rate at which iron increases, and compare tight the data spread in correlation equation is between the groups to see robustness of the data collection method.

I have data for the following:

DISEASE_STATE: (nominal) (0 = disease, 1 = control). Age (scalar) IRON_CONTENT (scalar).


Can someone please point me in the right direction? I have tried GLM but I don't know if it is right. I was checking the t-value in the interaction ([DISEASE_STATE = 0] * Age) as whether the regression lines are different. This is my code:

UNIANOVA IRONCONTENT BY DISEASE_STATE WITH Age /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /EMMEANS=TABLES(DISEASE_STATE) WITH(Age=MEAN) COMPARE ADJ(LSD) /PRINT=OPOWER ETASQ HOMOGENEITY DESCRIPTIVE PARAMETER /CRITERIA=ALPHA(.05) /DESIGN=DISEASE_STATE Age Age*DISEASE_STATE


Or if it's as simple as a t-test, can you only just get the slope and the standard error of the slope for both groups and do a calculation? if so, is this the same result as the code above?