Hello,
I would appreciate if someone could provide me with a better approach to solve this problem:
Creating a reference group(refgroup) from unexposed subjects(ids) and finding the odds ratio for the refgroup using logistic model
My main aims are thus are to
- Count the number of cases(ca case) and controls (pop cont) not exposed to any of the the 4 agents (a1, a2,a3 and a4 ) from the dataset agents_expt (Table 1) below. Exposed is 1 and unexposed is zero (0).
Results: 3 ca cases and 7 pop cont obtained(Table 2). -Step 1 of SAS code
b.Create/name the results obtained in Table 2(ie. subjects unexposed to any of the agents as a refgroup for the purpose of comparison.-Step 2 of SAS code.
Please, I would need help here: SAS created 2 refgroups(0,1) which I think is incorrect. The refgroup should be for subjects unexposed to any agents only; i.e. only 1 refgroup should be created.
- Find the estimate (odds ratio) for the refgroup.-step 3 of SAS code.
Specifically, I would like SAS to find the odds ratio for the refgroup (i.e. subjects unexposed to any of the agents) only (i.e.only 1 refgroup) using logistic regression.
Please, I would need the correct SAS code to solve the problem.
My dataset, code and log are found below; results are attached.
Thanks in advance for your expertise.
ak.
/* Logistic test ref group test*/
data agents_expt;
input id$ a1 a2 a3 a4 lung$ 14-21 income 23-29;
datalines;
os1 1 0 0 1 ca case 45424
os2 1 1 0 0 ca case 52877
os3 0 0 0 0 pop cont 25600
os4 1 0 0 1 pop cont 14888
os5 0 0 0 0 ca case 41036
os6 0 0 0 0 ca case 20365
os7 1 0 1 1 pop cont 16988
os8 0 0 0 0 ca case 100962
os9 1 0 1 0 pop cont 11230
os10 0 0 1 0 ca case 35850
os11 0 1 0 0 pop cont 28700
os12 0 0 0 0 pop cont 46320
os13 1 1 1 1 pop cont 24897
os14 0 0 0 0 pop cont 18966
os15 1 0 0 1 ca case 20540
os16 0 0 1 0 pop cont 150600
os17 1 1 1 1 pop cont 24897
os18 0 0 0 0 pop cont 17999
os19 0 0 0 0 pop cont 22540
os20 0 0 0 0 pop cont 158600
os21 0 0 0 0 pop cont 187365
os22 1 0 1 0 ca case 30580
;
run;
proc print data=agents_expt;
Title 'Table 1: Exposure of ids to 4 agents';
/*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/
proc freq data=agents_expt(where=(sum(a1,a2,a3,a4)=0));
tables lung;
title 'Table 2:Subjects unexposed to any of the 4 agents';
run;
/*Step 2:Using subjects unexposed to any of agents as a ref. group*/
proc sql;
create table t as
select
id, a1, a2, a3,a4,lung, income,
sum(a1,a2,a3,a4)=0 as refgroup
from agents_expt
;
quit;
proc print data=t;
title 'Table 3: original variables and ref group';
run;
proc freq data=t;
tables lung* refgroup;
title 'Table 4: freq of ca case and pop cont for ref group';
run;
/*Step 3: Finding odds ratio estimates for variables including ref.group*/
/* LOGISTIC REG. TEST*/
data logtest; set t;
if lung in ('ca case','pop cont');
run;
proc logistic data=logtest;
model lung(event='ca case') =refgroup;
Title 'Table 5: Estimates for ref. group';
run;
1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
72
73 /* Logistic test ref group test*/
74 data agents_expt;
75 input id$ a1 a2 a3 a4 lung$ 14-21 income 23-29;
76 datalines;
NOTE: The data set WORK.AGENTS_EXPT has 22 observations and 7 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
99 ;
100 run;
101
102
103 proc print data=agents_expt;
104 Title 'Table 1: Exposure of ids to 4 agents';
105
106 /*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/
NOTE: There were 22 observations read from the data set WORK.AGENTS_EXPT.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.48 seconds
cpu time 0.47 seconds
107 proc freq data=agents_expt(where=(sum(a1,a2,a3,a4)=0));
108 tables lung;
109 title 'Table 2:Subjects unexposed to any of the 4 agents';
110 run;
NOTE: There were 10 observations read from the data set WORK.AGENTS_EXPT.
WHERE SUM(a1, a2, a3, a4)=0;
NOTE: PROCEDURE FREQ used (Total process time):
real time 0.18 seconds
cpu time 0.17 seconds
111
112 /*Step 2:Using subjects unexposed to any of agents as a ref. group*/
113
114 proc sql;
115 create table t as
116 select
117 id, a1, a2, a3,a4,lung, income,
118 sum(a1,a2,a3,a4)=0 as refgroup
119 from agents_expt
120 ;
NOTE: Table WORK.T created, with 22 rows and 8 columns.
121 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.01 seconds
cpu time 0.02 seconds
122
123 proc print data=t;
124 title 'Table 3: original variables and ref group';
125 run;
NOTE: There were 22 observations read from the data set WORK.T.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.26 seconds
cpu time 0.24 seconds
126
127 proc freq data=t;
128 tables lung* refgroup;
129 title 'Table 4: freq of ca case and pop cont for ref group';
130 run;
NOTE: There were 22 observations read from the data set WORK.T.
NOTE: PROCEDURE FREQ used (Total process time):
real time 0.25 seconds
cpu time 0.23 seconds
131
132 /*Step 3: Finding odds ratio estimates for variables including ref.group*/
133
134 /* LOGISTIC REG. TEST*/
135 data logtest; set t;
136 if lung in ('ca case','pop cont');
137 run;
NOTE: There were 22 observations read from the data set WORK.T.
NOTE: The data set WORK.LOGTEST has 22 observations and 8 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
138
139 proc logistic data=logtest;
140 model lung(event='ca case') =refgroup;
141 Title 'Table 5: Estimates for ref. group';
142 run;
NOTE: PROC LOGISTIC is modeling the probability that lung='ca case'.
NOTE: Convergence criterion (GCONV=1E-8) satisfied.
NOTE: There were 22 observations read from the data set WORK.LOGTEST.
NOTE: PROCEDURE LOGISTIC used (Total process time):
real time 0.56 seconds
cpu time 0.51 seconds
143
144 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
156
