Hello All,
I am having difficulty with an interaction plot. I am trying to see if there is a difference in the change in pulmonary function in people with diabetes vs those without over, a 10 year time period. I wrote this to calculate the change.
data working4;
set working3;
change_fev1pp = fev1pp_Post_p3 - fev1pp_Post_p1;
change_fev1_FVC = fev1_FVC_post_p3 - Fev1_FVC_post_p1;
run;
I used proc glm to give me the type III table and the interaction plot for change in fev1pp.
proc glm data=working4;
class diabetes_P1(ref='No') finalgold_P1 (ref='GOLD 0');
model change_fev1pp = diabetes_P1 finalgold_p1 diabetes_P1*finalgold_p1;
lsmeans diabetes_P1 finalgold_p1 diabetes_P1*finalgold_p1 / pdiff;
format finalgold_p1 baseline_gold_stage. diabetes_P1 diabetes_baseline.;
run;
I get the type III table and an interaction plot.
I need this same output but after I adjust for several variables (age, gender, bmi, high bp, high cholesterol, corticosteroid use, smoking status). I first tried to do this using Proc glm
proc glm data=working4;
class diabetes_P1(ref='No') finalgold_P1(ref='GOLD 0') Gender(ref='1') BMI_P1(ref='Healthy')
highbloodpres_P1(ref='No') highcholest_P1(ref='No')
cortsterinhal_P1(ref='No') cortsteroral_P1(ref='No') smokcignow_P1(ref='No');
model change_fev1pp = diabetes_P1 finalgold_P1 diabetes_P1*finalgold_P1
BMI_P1 highbloodpres_P1 highcholest_P1 age_P1
cortsterinhal_P1 cortsteroral_P1 smokcignow_P1 gender;
lsmeans diabetes_P1 finalgold_p1 diabetes_P1*finalgold_p1 / pdiff;
format finalgold_P1 final_gold_stage. diabetes_P1 diabetes_final. BMI_P1
BMI_group. highbloodpres_P1 highbloodpres_group. highcholest_P1 highcholest_group. smokcignow_P1 smokcignow_group.
cortsterinhal_P1 cortsterinhal_group. cortsteroral_P1 cortsteroral_group.;
run;
and I get the type III table but not the interaction plot. Is this interaction plot not possible when including variables I'm adjusting for or did I do it wrong? Is there a better visual representation to show the change in fev1pp by GOLD stage over 10 years time in people with diabetes vs without?
I also tried to adjust for the variables in proc logistic, but that wasn't right either.
proc logistic data=working4;
class diabetes_P1 (ref ='No') finalgold_P1 (ref='GOLD 0') race (ref='1') Gender(ref='1') BMI_P3(ref='Healthy')
highbloodpres_P3(ref='No') highcholest_P3(ref='No')
cortsterinhal_P3(ref='No') cortsteroral_P3(ref='No') smokcignow_P3(ref='No');
model change_fev1pp = diabetes_P1 finalgold_p1 diabetes_P1*finalgold_p1
age_P3 BMI_P3 highbloodpres_P3 highcholest_P3
cortsterinhal_P3 cortsteroral_P3 smokcignow_P3 gender/ link=glogit;
lsmeans diabetes_P1 finalgold_p1 diabetes_P1*finalgold_p1 / pdiff;
format finalgold_p1 final_gold_stage. diabetes_P1 diabetes_baseline. BMI_P3
BMI_group. highbloodpres_P3 highbloodpres_group. highcholest_P3 highcholest_group. smokcignow_P3 smokcignow_group.
cortsterinhal_P3 cortsterinhal_group. cortsteroral_P3 cortsteroral_group. finalgold_P3 Baseline_GOLD_Stage.;
run;
I get this error.
ERROR: Computations are terminated because the number of response levels, 614, exceeds MAXRESPONSELEVELS=100.
NOTE: The SAS System stopped processing this step because of errors.
NOTE: There were 2864 observations read from the data set WORK.WORKING4.
NOTE: PROCEDURE LOGISTIC used (Total process time):
real time 0.19 seconds
user cpu time 0.17 seconds
system cpu time 0.02 seconds
memory 33575.15k
OS Memory 61600.00k
Timestamp 04/21/2024 10:06:27 PM
Step Count 525 Switch Count 0
Page Faults 0
Page Reclaims 8318
Page Swaps 0
Voluntary Context Switches 0
Involuntary Context Switches 0
Block Input Operations 0
Block Output Operations 40
81
82 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
Thanks.