Hello,
This is the corrected version of the last post. I am modelling refA not refB.
I finding the association between agents a1,a2,a3 and a4 exposures and lung cancer. Exposed = 1, unexposed =0. My ref. group(refA) is ids unexposed to any of the agents.
a. I am not sure whether my logistic regression model step 3b is right. I am modelling refA with lung-a1 association., then refA with lung-a2 association,etc.
b. Should the refA be considered as continuous or categorical(as I have done in step 3b of the model)?
Thanks in advance.
ak.
/* Logistic test ref group test*/
data agents_exp;
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;
/*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/
proc freq data= agents_exp(where=(sum(a1,a2,a3,a4)=0));
tables lung;
title 'Table 1: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,
sum(a1,a2,a3,a4)=0 as refA
from agents_exp
;
quit;
proc print data=t;
title 'Table 2: original variables and ref group';
run;
/*proc freq data=t;
tables lung* refA lung*a1;
title 'Table 3: freq of ca case and pop cont for ref group';
run;*/
/*Step 3a: Finding odds ratio estimates for variables including ref.group*/
data logtest; set t;
if lung in ('ca case','pop cont');
run;
/* Step 3b:*/
proc logistic data=logtest;
class refA (param=ref ref ='0');
model lung(event='ca case') = a1 refA;
Title 'Table 3b: Estimates for ref. group';
run;
1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
72
73 /* Logistic test ref group test*/
74 data agents_exp;
75 input id$ a1 a2 a3 a4 lung$ 14-21 income 23-29;
76 datalines;
NOTE: The data set WORK.AGENTS_EXP has 22 observations and 7 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds
99 ;
100 run;
101
102 /*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/
103 proc freq data= agents_exp(where=(sum(a1,a2,a3,a4)=0));
104 tables lung;
105 title 'Table 1:Subjects unexposed to any of the 4 agents';
106 run;
NOTE: There were 10 observations read from the data set WORK.AGENTS_EXP.
WHERE SUM(a1, a2, a3, a4)=0;
NOTE: PROCEDURE FREQ used (Total process time):
real time 0.23 seconds
cpu time 0.20 seconds
107 /*Step 2:Using subjects unexposed to any of agents as a ref. group*/
108
109 proc sql;
110 create table t as
111 select
112 id, a1, a2, a3,a4,lung,
113 sum(a1,a2,a3,a4)=0 as refA
114 from agents_exp
115 ;
NOTE: Table WORK.T created, with 22 rows and 7 columns.
116 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.02 seconds
cpu time 0.02 seconds
117
118 proc print data=t;
119 title 'Table 2: original variables and ref group';
120 run;
NOTE: There were 22 observations read from the data set WORK.T.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.49 seconds
cpu time 0.47 seconds
121
122 /*proc freq data=t;
123 tables lung* refA lung*a1;
124 title 'Table 3: freq of ca case and pop cont for ref group';
125 run;*/
126
127 /*Step 3a: Finding odds ratio estimates for variables including ref.group*/
128
129 data logtest; set t;
130
131 if lung in ('ca case','pop cont');
132 run;
NOTE: There were 22 observations read from the data set WORK.T.
NOTE: The data set WORK.LOGTEST has 22 observations and 7 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.02 seconds
133
134
135 /* Step 3b:*/
136 proc logistic data=logtest;
137 class refA (param=ref ref ='0');
138 model lung(event='ca case') = a1 refA;
139 Title 'Table 3b: Estimates for ref. group';
140 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 0.50 seconds
141
142
143 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
155
