Hello, 1. I am creating 2 different groups; refgroupA and refgroup B.I have been able to create refgroupA but I would need assistance for refgroup B. Refgroup B in the results(attached) is incorrect.   There are 3 agents (a1exp,a2exp and a3exp), their levels and categories of exposures. 0=unexposed, 1 is exposed with levels 1=high and 2=low. Refgroup A are ids(cases and controls(cont) not exposed to agent 1(a1exp): ie. a single reference group used for the evaluated agents (a2exp and a3exp). Refgroup B are ids exposed to agent 1(a1exp) but not to agent under analysis ie. a2exp and a3exp.[Actually there are many agents but I am using only 3 of them as a test]. The idea of these refgroups is to check of the ORs are lower when using refgroup A in the analysis, in comparison with ORs obtained with regroup B. refgroupB created is not right because ids exposed to a1exp not a2exp are os2, os6 and os12; Ids exposed to a1exp not a3exp are os4,os6 and os13. Help needed here, please for the refgroupB. 2. Help also needed when using refgroupA and refgroupB in analysis to be able to fill in   the OR table (Table 3) attached.   ? After creating the refgroups, do I have to merge the regroup results with original data(expinfo) to be able to fill in the table? I have no clue. Please help. Thanks. ak. data expinfo; input id$ 1-4 a1exp 6-7 a1exp_level$ 8-17 a1exp_cat 19-20 a2exp 26-27 a2exp_level$ 28-32 a2exp_cat 39-40 a3exp 46-47 a3exp_level$ 48-50 a3exp_cat 59-60 lung$ 68-72; datalines; os1 0 unexposed 0 1 high 1 0 unexposed 0 case os2 1 low 2 0 unexposed 0 1 low 2 case os3 0 unexposed 0 0 unexposed 0 0 unexposed 0 case os4 1 high 1 1 low 2 0 unexposed 0 cont os5 0 unexposed 0 0 unexposed 0 1 high 1 cont os6 1 low 2 0 unexposed 0 0 unexposed 0 case os7 1 low 2 1 high 1 1 low 2 case os8 0 unexposed 0 0 unexposed 0 0 unexposed 0 case os9 0 unexposed 0 0 unexposed 0 0 unexposed 0 cont os10 1 high 1 1 low 2 1 low 2 cont os11 0 unexposed 0 0 unexposed 0 1 high 1 case os12 1 low 2 0 unexposed 0 1 high 1 case os13 1 high 1 1 low 2 0 unexposed 0 case os14 0 unexposed 0 0 unexposed 0 0 unexposed 0 cont os15 0 unexposed 0 0 unexposed 0 0 unexposed 0 cont os16 1 high 1 1 low 2 1 high 1 cont os17 0 unexposed 0 1 high 1 1 low 2 cont os18 0 unexposed 0 0 unexposed 0 0 unexposed 0 cont ; run; proc freq data=expinfo; where a1exp=0; tables lung; title 'Table 1:Subjects unexposed to a1exp'; run; proc sql; create table t as select id, a1exp, a2exp,a3exp,lung, a1exp=0 as refgroupA, a1exp ne 0 and a2exp=0 and a1exp ne 0 and a3exp=0 as refgroupB from expinfo ; quit; proc print data=t; title 'Table 2: original variables and refgroupA and refgroupB; refgroupB is not correct'; run; 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 74 data expinfo; 75 input id$ 1-4 a1exp 6-7 a1exp_level$ 8-17 a1exp_cat 19-20 76 a2exp 26-27 a2exp_level$ 28-32 a2exp_cat 39-40 a3exp 46-47 a3exp_level$ 48-50 a3exp_cat 59-60 77 lung$ 68-72; 78 datalines;   NOTE: The data set WORK.EXPINFO has 18 observations and 11 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds     97 ; 98 run; 99 100 101 102 proc freq data=expinfo; where a1exp=0; 103 tables lung; 104 title 'Table 1:Subjects unexposed to a1exp'; 105 run;   NOTE: There were 10 observations read from the data set WORK.EXPINFO. WHERE a1exp=0; NOTE: PROCEDURE FREQ used (Total process time): real time 0.26 seconds cpu time 0.25 seconds     106 107 proc sql; 108 create table t as 109 select 110 id, a1exp, a2exp,a3exp,lung, 111 a1exp=0 as refgroupA, 112 113 a1exp ne 0 and a2exp=0 and a1exp ne 0 and a3exp=0 as refgroupB 114 115 from expinfo 116 ; NOTE: Table WORK.T created, with 18 rows and 7 columns.   117 quit; NOTE: PROCEDURE SQL used (Total process time): real time 0.01 seconds cpu time 0.01 seconds     118 119 proc print data=t; 120 title 'Table 2: original variables and refgroupA and refgroupB; 121 refgroupB is not correct'; 122 run;   NOTE: There were 18 observations read from the data set WORK.T. NOTE: PROCEDURE PRINT used (Total process time): real time 0.35 seconds cpu time 0.35 seconds     123 124 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 136       ... View more

  Hello, I would appreciate if someone could help me with the SAS code in logistic regression to find the estimate log odds/odds ratio of a comparison/reference group (refgroup) above. I have the same refgroup for the 2 agents(a1exp and a2exp). I used a similar approach to the solution to my previous question that I posted on the forum and which was answered by someone. I am posting another question quite different from what I posted before. Unexposed = 0, exposure levels: 1= high and 2=low. Thanks in advance. ak.   Main focus: Refgroup column; how to compute the ORs using logistic regression.   Reference group(refgroup) is composed of subjects (ids) not exposed to either of the agents(a1exp or a2exp). 2 ca cases (cases) and 6 pop cont(controls) met the criterion. Please find below my code and log. Results are attached(Table 5: Exposure levels).   data expinfo; input id$ 1-4 a1exp 6-7 a1exp_level$ 8-17 a1exp_cat 19-20 a2exp 26-27 a2exp_level$ 28-32 a2exp_cat 39-40 lung$ 48-55; datalines; os1 0 unexposed 0 1 high 1 ca case os2 1 low 2 0 unexposed 0 ca case os3 0 unexposed 0 0 unexposed 0 pop cont os4 1 high 1 1 low 2 pop cont os5 0 unexposed 0 0 unexposed 0 pop cont os6 1 low 2 0 unexposed 0 ca case os7 1 low 2 1 high 1 ca case os8 0 unexposed 0 0 unexposed 0 ca case os9 0 unexposed 0 0 unexposed 0 pop cont os10 1 high 1 1 low 2 pop cont os11 0 unexposed 0 0 unexposed 0 ca case os12 1 low 2 0 unexposed 0 ca case os13 1 high 1 1 low 2 ca case os14 0 unexposed 0 0 unexposed 0 pop cont os15 0 unexposed 0 0 unexposed 0 pop cont os16 1 high 1 1 low 2 pop cont os17 0 unexposed 0 1 high 1 pop cont os18 0 unexposed 0 0 unexposed 0 pop cont ; run; /*proc print data=expinfo; Title 'Table 1: Exposure of ids to 2 agents';*/ /*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/ proc freq data=expinfo(where=(sum(a1exp,a2exp)=0)); tables lung; title 'Table 1:Subjects unexposed to either of the 2 agents'; run; /*Step 2:Using subjects unexposed to any of agents as a ref. group*/ proc sql; create table t as select id, a1exp, a2exp,lung, sum(a1exp,a2exp)=0 as refgroup from expinfo ; quit; proc print data=t; title 'Table 2a: original variables and ref group'; run; proc freq data=t; tables lung* refgroup; title 'Table 2b: freq of ca case and pop cont for ref group'; run; proc freq data=expinfo; tables lung* a1exp_level lung*a1exp_cat lung* a2exp_level lung*a2exp_cat ; title 'Table 3: freq of ca case and pop cont for vs lung'; run; data logtest; set t; if lung in ('ca case','pop cont'); run; proc logistic data=logtest; model lung(event='ca case') =refgroup; Title 'Table 4: Estimates for ref. group'; run; 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 data expinfo; 74 input id$ 1-4 a1exp 6-7 a1exp_level$ 8-17 a1exp_cat 19-20 75 a2exp 26-27 a2exp_level$ 28-32 a2exp_cat 39-40 lung$ 48-55; 76 datalines;   NOTE: The data set WORK.EXPINFO has 18 observations and 8 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds     95 ; 96 run; 97 98 /*proc print data=expinfo; 99 100 Title 'Table 1: Exposure of ids to 2 agents';*/ 101 102 /*Step 1: Finding number of cases and controls unexposed to agents(a1,a2,a3 and a4)*/ 103 proc freq data=expinfo(where=(sum(a1exp,a2exp)=0)); 104 tables lung; 105 title 'Table 1:Subjects unexposed to either of the 2 agents'; 106 run;   NOTE: There were 8 observations read from the data set WORK.EXPINFO. WHERE SUM(a1exp, a2exp)=0; NOTE: PROCEDURE FREQ used (Total process time): real time 0.20 seconds cpu time 0.20 seconds     107 108 109 110 /*Step 2:Using subjects unexposed to any of agents as a ref. group*/ 111 112 proc sql; 113 create table t as 114 select 115 id, a1exp, a2exp,lung, 116 sum(a1exp,a2exp)=0 as refgroup 117 from expinfo 118 ; NOTE: Table WORK.T created, with 18 rows and 5 columns.   119 quit; NOTE: PROCEDURE SQL used (Total process time): real time 0.01 seconds cpu time 0.01 seconds     120 121 proc print data=t; 122 title 'Table 2a: original variables and ref group'; 123 run;   NOTE: There were 18 observations read from the data set WORK.T. NOTE: PROCEDURE PRINT used (Total process time): real time 0.22 seconds cpu time 0.22 seconds     124 125 proc freq data=t; 126 tables lung* refgroup; 127 title 'Table 2b: freq of ca case and pop cont for ref group'; 128 run;   NOTE: There were 18 observations read from the data set WORK.T. NOTE: PROCEDURE FREQ used (Total process time): real time 0.16 seconds cpu time 0.15 seconds     129 proc freq data=expinfo; 130 tables lung* a1exp_level lung*a1exp_cat 131 lung* a2exp_level lung*a2exp_cat ; 132 title 'Table 3: freq of ca case and pop cont for vs lung'; 133 run;   NOTE: There were 18 observations read from the data set WORK.EXPINFO. NOTE: PROCEDURE FREQ used (Total process time): real time 0.52 seconds cpu time 0.52 seconds     134 135 data logtest; set t; 136 if lung in ('ca case','pop cont'); 137 run;   NOTE: There were 18 observations read from the data set WORK.T. NOTE: The data set WORK.LOGTEST has 18 observations and 5 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds     138 139 proc logistic data=logtest; 140 model lung(event='ca case') =refgroup; 141 Title 'Table 4: 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 18 observations read from the data set WORK.LOGTEST. NOTE: PROCEDURE LOGISTIC used (Total process time): real time 0.44 seconds cpu time 0.40 seconds     143 144 145 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 157     ... View more

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     ... View more

Hello, I would appreciate if someone could provide me with a better approach to solve the problem. My main aims are  a. 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 reference group(refgroup) for the purpose of comparison.-Step 2 of SAS code c. Find the estimates (odds ratio) for the refgroup and other variables including income.-step 3 of SAS code. Looks like my SAS code are too long to achieve the above aims.   I would appreciate if someone could provide me with a better approach to solve the problem.   *Pls note: For the purpose of  this test approach,  let us ignore the warning:quasi-separation of points(as there are inadequate data) . If the code works for this test data, I am sure it will work for the original dataset too.   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;/*P stands for Pooled*/ if lung in ('ca case','pop cont'); run; proc logistic data=logtest; /*class cla_scat (param=ref ref ='0');*/ /*model lung(event='Ca case') = cla_expf age cigcsi;*/ model lung(event='ca case') =a1 a2 a3 a4 refgroup income; Title 'Table 5: Estimates for variables including ref. group'; run;           OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;  72          73          74         /* Logistic test ref group test*/  75          data agents_expt;  76         input id$ a1 a2 a3 a4  lung$ 14-21 income 23-29;  77         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            100        ;  101        run;  102        proc print data=agents_expt;  103        Title 'Table 1: Exposure of ids to 4 agents';  104         105          /*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           0.27 seconds        cpu time            0.27 seconds           106        proc freq data=agents_expt(where=(sum(a1,a2,a3,a4)=0));  107             tables lung;  108        title 'Table 2:Subjects unexposed to any of the 4 agents';  109        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           0.13 seconds        cpu time            0.11 seconds           110          111        /*Step 2:Using subjects unexposed to any of agents as a ref. group*/  112         113        proc sql;  114        create table t as  115          select  116            id, a1, a2, a3,a4,lung, income,  117            sum(a1,a2,a3,a4)=0 as refgroup  118             from agents_expt  119             ;  NOTE: Table WORK.T created, with 22 rows and 8 columns.    120             quit;  NOTE: PROCEDURE SQL used (Total process time):        real time           0.01 seconds        cpu time            0.02 seconds           121         122           proc print data=t;  123           title 'Table 3: original variables and ref group';  124           run;    NOTE: There were 22 observations read from the data set WORK.T.  NOTE: PROCEDURE PRINT used (Total process time):        real time           0.22 seconds        cpu time            0.23 seconds           125         126            proc freq data=t;  127            tables lung* refgroup;  128            title 'Table 4: freq of ca case and pop cont for ref group';  129            run;    NOTE: There were 22 observations read from the data set WORK.T.  NOTE: PROCEDURE FREQ used (Total process time):        real time           0.15 seconds        cpu time            0.14 seconds           130         131        /*Step 3: Finding odds ratio estimates for variables including ref.group*/  132         133        /* LOGISTIC REG. TEST*/  134        data logtest; set t;/*P stands for Pooled*/  135        if lung in ('ca case','pop cont');  136        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           137         138         proc logistic data=logtest;  139        /*class cla_scat (param=ref ref ='0');*/  140        /*model lung(event='Ca case') = cla_expf age cigcsi;*/  141        model lung(event='ca case') =a1 a2 a3 a4 refgroup income;  142        Title 'Table 5: Estimates for variables including ref. group';  143        run;    NOTE: PROC LOGISTIC is modeling the probability that lung='ca case'.  WARNING: There is possibly a quasi-complete separation of data points. The maximum likelihood estimate may not exist.  WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based on the last maximum likelihood           iteration. Validity of the model fit is questionable.  NOTE: There were 22 observations read from the data set WORK.LOGTEST.  NOTE: PROCEDURE LOGISTIC used (Total process time):        real time           0.44 seconds        cpu time            0.41 seconds           144         145         146        OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;  158            ... View more