Unix Banner for interesting titles

ASCII Banner 1 , 2

.'|. . '|| .||. .... .||. .... .... .. ... .. || || '' .|| || ||. ' '' .|| || || .' '|| || .|' || || . '|.. .|' || || || |. || .||. '|..'|' '|.' |'..|' '|..'|' .||. ||. '|..'||. || .... .. ... ... . ... .. ... .... '' .|| || || || || || || || '' .|| .|' || || || |'' || || || .|' || '|..'|' .||. ||. '||||. .||. .||. ||. '|..'|' .|....' __ _ _ _ / _| __ _| |_ ___ __ _ _ __ __| | __ _ _ __ __ _(_)_ __ __ _ | |_ / _` | __/ __| / _` | '_ \ / _` | / _` | '_ \ / _` | | '_ \ / _` | | _| (_| | |_\__ \ | (_| | | | | (_| | | (_| | | | | (_| | | | | | (_| | |_| \__,_|\__|___/ \__,_|_| |_|\__,_| \__,_|_| |_|\__, |_|_| |_|\__,_| Have fun. Don´t forget to bookmark this website :)

---

Make results more presentable

SAS regression output requires additional steps to make it presentable. In previous posts, I have highlighted how to only get the results for variables of interest. However, these results are in row format

Obs F1 or lci uci p_value

1 exp1 1.202 1.110 1.34 .001
2 exp2 1.340 1.202 1.56 .001
3 exp3 1.560 1.340 1.89 .001
4 exp4 1.890 1.560 1.98 .001



This output need to be further transposed in Excel to get the results in following format.

Obs exp0 exp1 exp2 exp3 exp4

1 1 1.2020 1.3400 1.5600 1.8900
2 1.11,1.34 1.202,1.56 1.34,1.89 1.56,1.98
3 0.0010 0.0010 0.0010 0.0010


The following program eliminates that

proc import datafile="C:\Documents and Settings\mkaushik\Desktop\Output results.xls" out=auto replace;
run;
data inter /* / view=intermediate*/;
set auto;
orc= put(or,6.4);
pvaluec= put(p_value,6.4);
new=compress(lci||','||uci);
output; *output the input record;
if _n_=1 then do;
F1='exp0';
or=1; *set values for your added obs;
lci=.;uci=.;p_value=.;
orc="1";
pvaluec=" ";
new=" ";
output; *output your added obs;
end;
proc sort;
by F1;
run;
data inter;
set inter;
array Value (*) orc new pvaluec;
do id =1 to 3;
_value_ = value [id]; * since first numeric is that date;
F1=F1;
output;
end;
drop or p_value _name_;
run;
proc print data=inter;
run;

proc sort data=inter;
by id;
run;
proc transpose data=inter out=outset(drop=id _name_) ;
by id ;
id F1 ;
var _value_;
run;
proc print data=outset;
run;

Correspondence between genmod and logistic

I have been exploring this for my work. I found some guidance here. I am including some details here.
data drug;
input drug$ x r n;
cards;
A .1 1 10
A .23 2 12
A .67 1 9
B .2 3 13
B .3 4 15
B .45 5 16
B .78 5 13
C .04 0 10
C .15 0 11
C .56 1 12
C .7 2 12
D .34 5 10
D .6 5 9
D .7 8 10
E .2 12 20
E .34 15 20
E .56 13 15
E .8 17 20
;

proc genmod data=drug;
class drug;
model r/n=x drug / dist=binomial link=logit;
estimate 'A vs E' drug 1 0 0 0 -1/exp;
run;

proc logistic data=drug;
class drug/param=ref;
model r/n=x drug;
run;

/* generates dummy variables coded as follows
drug A 1 0 0 0
B 0 1 0 0
C 0 0 1 0
D 0 0 0 1
E 0 0 0 0 */


proc logistic data=drug;
class drug;
model r/n=x drug;
run;


/* generates dummy variables coded as follows

Class Value Design Variables

drug A 1 0 0 0
B 0 1 0 0
C 0 0 1 0
D 0 0 0 1
E -1 -1 -1 -1
*/


However, the results (Odds ratio) are going to be the same. Accessible help on writing contrast statements is here.

Proc tabulate/proc report

I have been trying to learn these new tools.

Here is a pdf with clear instructions and uses of both.

Some available options are ACROSS, ANALYSIS, CENTER, COLOR, COMPUTED, CSS, CV, DESCENDING, DISPLAY, EXCLUSIVE, F, FLOW, FORMAT, GROUP, ID, ITEMHELP, LEFT, MAX, MEAN, MEDIAN, MIN, MISSING, N, NMISS, NOPRINT, NOZERO, ORDER, P1, P10, P25, P5, P50, P75, P90, P95, P99, PAGE, PCTN, PCTSUM, PRELOADFMT, PRT, Q1, Q3, QRANGE, RANGE, RIGHT, SPACING, STD, STDERR, STYLE, SUM, SUMWGT, T, USS, VAR, WEIGHT, WGT, WIDTH.

Macro to output only relevant results to ods

/** following macro runs logistic regression and outputs the results from only the relevant variables to the html file. In this case, I am running regression with various variables but keeping age in all the models. Age is not the variable of interest. */

%macro jncht(dataname,var1);
title "Age and sex adjusted &var1";
ods select OddsRatio ParameterEstimates;
proc logistic data=&dataname ;
model jncht=&var1 ahage ahsex ;
ods output OddsRatios=orrr;
ods output ParameterEstimates=Param;
run;

data param;
set param;
drop DF Estimate StdErr;
run;

proc sort;
by variable;

data orrr;
set orrr;
variable=effect;
drop effect;
proc sort;
by variable;
run;

data new;
merge param orrr;
by variable;
run;
%let cuts=%SUBSTR(&var1,1,4);

ods html select all;
title " age and sex adjusted &var1";
proc print data=new;
var variable OddsRatioEst LowerCL UpperCL ProbChiSq;
where variable like "%NRBQUOTE(%)&cuts%NRBQUOTE(%)";
run;
ods html exclude all;
proc datasets;
delete param orrr new;
%mend ;

Invocation of this macro.
/*include the following statement in the beginning of the program*/
ods html file ="%sysfunc
(reverse(%sysfunc(substr(%sysfunc(reverse(%sysfunc(reverse(%scan(%sysfunc(reverse(%sysfunc(getoption(sysin)))),1,/))))),5)))).html"
STYLE=MINIMAL;

data...;
.
.
.;
%jncht(trott1,&wstci_)

/*Where &wstci_ is a macro variable and equals 'wstci1 wstci2 wstci3'. */

Wildcards in different situations

This is a broad area to handle in one posting but here are few links that I found useful:

Matching with a wildcard using Perl regular expression A possible problem with this method is inability of this method to handle macro variables.

Matching with like and percent (%) It is used in the next post.

Using wildcards to read many files into one SAS data set

Interactions in logistic regression using proc genmod

I have been trying to do logistic regression with interactions. Since this would have required a lot of dummy coding in proc logistic, I used proc genmod.

proc genmod;
class ahsex(ref=first) ah66a qtype &smok_ &alco_;
model jncht= wstrs wstrs*ahsex ahsex ah66a ahage &smok_ &alco_ WLTHINDF QTYPE/ error=bin link=logit type3;
run;

Another way to encode the interaction term and the main effects would be using "wstrs|ahsex". This equals "wstrs wstrs*ahsex ahsex".
The ref option could be replaced with (ref="1") . Specifying more than one REF= variable option in the CLASS statement could be a problem.

In case you are wondering, &smok_ refer to the macro variable I created earlier in the code as follows:
%let &sm0k= smok1 smok2 smok3 smokm;