source: main/adopters/nj/trunk/src/main/ibisq/qModules3/hiv/RateCrude100K.def @ 26872

#RateCrude100K.def
#Calculates crude rates for records that have been filtered by IBIS-Q (data=tmp)
#Uses the IBIS-Q data_frame for cross1 and cross2
#NM_ = New Mexico cell suppression version
#Applies NM cell suppression rules
#Outputs redflag var based on RSE
#
f type special
#########################################
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1 script
OPTIONS MPRINT MLOGIC SYMBOLGEN NONUMBER NODATE PAGESIZE=4000;
OPTION SPOOL;

 ************************** 1. TMP ******************************;
 * The dataset 'tmp' is the numerator dataset that has been read ;
 * in already by ibis-q. Any filters have already been applied.  ;
 * The proc summary counts deaths by cross1 and cross2.          ;
 ****************************************************************;
        proc summary data=tmp;
                var x;
                class %cross1% 
                ?cross2? %cross2%
                ;
                output out=tmp (drop=_TYPE_ _FREQ_) sum=count;
        proc sort data=tmp out=sorted; by %cross1% 
                ?cross2? %cross2%
                ; run;
        proc print data=sorted noobs; 
                title1 '---------------------------------'; 
                title2 '1. TMP - numerator dataset'; 
                run;
 
 *********************** 2. data_frame **************************;
 * df_%cross1%%cross2% is a dataset created by IBIS-Q.           ;
 * It consists of %cross1% and %cross2% (if the user specified   ;
 * %cross2%) and a variable named "count" that is set to "0".    ;
 * The results of the proc summary must be merged with the       ;
 * df_%cross1%%cross2% dataset.                                  ;
 * We don't use the cross1 and cross2 subtotals, anymore, we     ;
 * only use the grand total in the but Kendo table result, but   ;
 * don't delete them because it will mess up the table marginal  ;
 * cell suppression - it will suppress table rows in the table   ;
 * body when it doesn't find the cross1 and cross2 totals.       ;
 ****************************************************************;
        data frame;
                set df_%cross1%%cross2%;
                run;
        proc sort data=frame; by %cross1% 
                ?cross2? %cross2%
                ; run;
        proc print data=frame noobs; 
                title2 '2. Data Frame'; 
                run;

        *set length so that values don't get truncated;
        *listing frame dataset first will retain all records in frame;
        data tmp;
                length count 8;
                merge frame sorted; 
                by %cross1% 
                   ?cross2? %cross2%
                ;
                run;
        proc print data=tmp noobs; 
                title2 '2. tmp, after merged with frame'; 
                run;

 *************** 3. Flag variable and popcross macro *************;
 * The flag variable checks the cross variables for presence of   ;
 * variables that are found in the population dataset. IBIS-q     ;
 * created popcross vars based on info from the .CFG file.        ;
 * The popcross macro will merge the numerator and denominator    ;
 * data, matching up the appropriate values of the cross vars.    ;
 *****************************************************************;
        %let flag=0;
        ?popcross1? %let flag=1;
        ?popcross2? %let flag=1;
        ?popcross1? ?popcross2? %let flag=2;

        %macro popcross;

        %if &flag=0 %then %do;
                proc summary data=poptmp;
                        var popcount;
                        output out=pop (drop=_TYPE_ _FREQ_) sum=popcount;
                run;
                proc sql;
                        create table numbers as
                        select tmp.*, pop.*
                        from tmp, pop
                quit;
        %end;

        %if &flag=1 %then %do;
                proc summary data=poptmp;
                        var popcount;
                        class %popcross1% %popcross2%;
                        output out=pop (drop=_TYPE_ _FREQ_) sum=popcount;
                run;
                proc sql;
                        create table numbers as
                        select tmp.*, pop.*
                        from tmp left join pop
                        on
                        ?popcross1? tmp.%cross1%=pop.%popcross1%; 
                        ?popcross2? tmp.%cross2%=pop.%popcross2%;  
          quit; 
        %end;

        %if &flag=2 %then %do;
                proc summary data=poptmp;
                        var popcount;
                        class %popcross1% %popcross2%  ;
                        output out=pop (drop=_TYPE_ _FREQ_) sum=popcount;
                run;
                proc sql;
                        create table numbers as
                        select tmp.*, pop.*
                        from tmp left join pop
                        on
                        tmp.%cross1%=pop.%popcross1% and
                        tmp.%cross2%=pop.%popcross2%;
                quit;
        %end;
        %mend;
        %popcross;

        proc print data=numbers noobs; 
                title2 '3. numbers, after pop merged with tmp'; 
                run;

 ********************** 4. tmp, again ****************************;
 * Create the output variables for the IBIS xml/map file.         ;
 *****************************************************************;
        data rate;
                set numbers;
                        if count>0 then do;
                                rate=count/popcount;
                                rateper=(rate*100000);
                        end;
                        if count<=0 then do;
                                rate=3/popcount;
                                rateper=0;
                        end;
                stderr=sqrt(rate*(1-rate)/popcount)*100000;
                t1=(rateper-(1.96*stderr)); 
                if (t1<0) then t1=0; 
                LL=put(t1, 8.2);
                UL=put((rateper+(1.96*stderr)), 8.2);
                LL=compress(LL);
                UL=compress(UL);
                n=count;        *ibis-q needs a count variable named 'n';

 *********************** 5. Red Flag *****************************;
 * redflag is the statistical stability indicator based on the    ;
 * relative standard error (RSE, or coefficient of variation).    ;
 * Redflag values created here are converted to images or special ;
 * characters in IBIS-View application XSLTfiles, for instance:   ;
 * (xslt\html\query\module\result\ResultPage.xslt, ...Values.xslt ;
 *****************************************************************;
/*              if count>0 then do;
                        rse=(stderr/rateper);
                        redflag=put('', $12.); 
                        if rse>.3 then redflag=put('Unstable', $12.);
                        if rse>.5 then redflag=put('VeryUnstable', $12.);
                        if stderr=. then redflag=put('Unstable', $12.); 
                end;
                if count<=0 then redflag=put('Unstable', $12.);   *no variance, n=0, rse=div by zero;
        run;
        proc print data=rate noobs; 
                title2 '2. rate, rate rateper stderr UCL LL calculated'; 
                run;
*/
 ************* 6. New Mexico Small Numbers Rule ********************;
 * Suppress cells if the numerator in (1 2 3) AND the denominator   ;
 * is less than 20. For Counts, must run the crude rate code to     ;
 * capture the denominator, but only output the N. ZW’s program     ;
 * uses ".A" to identify cells for suppression. I have co-opted     ;
 * his method so I can use the NM logic for cell suppression instead;
 * of the standard IBIS logic. And I need to use ZW's program       ;
 * because it will suppress the table marginals that can be used to ;
 * calculate the suppressed cells. If this code is used, the .def   ;
 * file should have the "NM_" prefix. Needs suppressed_variabes     ;
 * code at the end of this file to work.                            ;
 *******************************************************************;
        data tmp;
                set rate;
                if  popcount ne . and 0<n<20 then do;
                        rateper = .A;
                        n = .A;
                        popcount = .A;
                        *LL = .A;
                        *UL = .A;
                        LL = put('**', 8.0);
                        UL = put('**', 8.0);

                *Only one value attribute is allowed - so if suppressed, overwrite unstable;
                *This also puts ** in record code column for suppressed rows, and adds footnote;
                        redflag = put('Suppressed', $12.);
                end;
                *if pop=. then redflag=put('', $12.); *no value attribute for missing crossby values;
        proc print data=tmp noobs;  title2 '6. TMP - final dataset to pass to IBIS View app'; 
        run;

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# definition for output file
f out_variable rateper
f xml_out_map_file XMLRate100KLow.map
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f out_detail lbl_not_used__see_xml_out_map_file
  rateper 15.1
  LL 15.3
  UL 15.3
  n 15.0
  popcount 15.0
  redflag 12.0
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 ****************** 7. SUPPRESSED VARIABLES *************************;
 * ZW's CGI program must be told how many variables it will need to  ;
 * suppress and which ones they are. NOTE: If the SAS code, above, is;
 * commented out, these lines can be left in the .def file without   ;
 * causing any problems. They will only be used if the SAS code,     ;
 * above is active, OR if the small_num and small_pop parameters     ;
 * are active in the .CFG file, and with non-zero values.            ;
 ********************************************************************;
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1 suppressed_variables 5
  rateper
  LL
  UL
  n
  pop
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