Changeset 19929 in main for adopters/mt/trunk/src/main/backend_qModules/birth23/MT_Average_data_frame.def

Timestamp:

03/02/20 15:03:56 (2 years ago)

Author:

Paul Leo

Message:

Tmp commit, only use in test....
Testing whether or not using T distribution a) works b) agrees with MT VS calculation of confidence intervals in birth calculations when count is between 20 and 100

File:

• adopters/mt/trunk/src/main/backend_qModules/birth23/MT_Average_data_frame.def (modified) (4 diffs)

adopters/mt/trunk/src/main/backend_qModules/birth23/MT_Average_data_frame.def

@@ -141 +141 @@
         %popcross;
 proc print data=rate noobs;  title2 '3. merged tmp and pop prior to cell suppression'; 
+
+ ********************** 4. tmp, again ****************************;
+ * Create the output variables for the IBIS xml/map file.         ;
+ * The following uses T distribution, for count, but when count   ;
+ * is above 30, it is really using normal distribution            ;
+ *****************************************************************;
+        data tmp;
+                set rate;
+ 
+ *****************************************************************;
+ * Student's t distribution. df=count-1. The "Z" value is really  ;
+ * the critical value of "t", two tailed, with an alpha of 0.025. ;
+ *****************************************************************;
+                     if count=1  then Z=  .;
+                else if count=2  then Z= 12.706;
+                else if count=3  then Z=  4.303;
+                else if count=4  then Z=  3.182;
+                else if count=5  then Z=  2.776;
+                else if count=6  then Z=  2.571;
+                else if count=7  then Z=  2.447;
+                else if count=8  then Z=  2.365;
+                else if count=9  then Z=  2.306;
+                else if count=10 then Z=  2.262;
+                else if count=11 then Z=  2.228;
+                else if count=12 then Z=  2.201;
+                else if count=13 then Z=  2.179;
+                else if count=14 then Z=  2.160;
+                else if count=15 then Z=  2.145;
+                else if count=16 then Z=  2.131;
+                else if count=17 then Z=  2.120;
+                else if count=18 then Z=  2.110;
+                else if count=19 then Z=  2.101;
+                else if count=20 then Z=  2.093;
+                else if count=21 then Z=  2.086;
+                else if count=22 then Z=  2.074;
+                else if count=23 then Z=  2.069;
+                else if count=24 then Z=  2.064;
+                else if count=25 then Z=  2.060;
+                else if count=26 then Z=  2.056;
+                else if count=27 then Z=  2.052;
+                else if count=28 then Z=  2.048;
+                else if count=29 then Z=  2.045;
+                else if count=30 then Z=  2.042;
+                else if count>30 then Z=  1.96;
+
+                t1=mean-(Z*stderr);
+                if (t1<0) then t1=0;
+                if count in (0 1) then t1=.;
+                LL=put(t1, 8.2);
+                UL=put((mean+(z*stderr)), 8.2);
+                LL=compress(LL);
+                UL=compress(UL);
+                n=count;        *ibis-q needs a count variable named 'n';
+                
+        proc print data=tmp;  title2 '4. tmp again - t1=mean*stderr, LL,UL,n before suppression'; 
+        run;
         run;
         
- ********************** 4. tmp, again Redflag and cell suppression *************;
+ ********************** 5. tmp, again Redflag and cell suppression *************;
  * Create the output variables for the IBIS xml/map file.                                               ;
  * Add Redflag                                                                                                                                  ;
@@ -183 +239 @@
 
         data tmp;
-                set rate;
+                set tmp;
                 n=count;  *ibis-q needs a count variable named 'n';
 
@@ -209 +265 @@
 
                         if 20<=count<=100 then do; 
-                        * for events between 20 and 100, use Poisson to calculate confidence intervals;
-
-                                t1= GAMINV(.025,count)/popcount*1000;
-                                if (t1<0) then t1=0;
-                                LL=put(t1, 8.2);
-                                UL=put(( GAMINV(.975,count)/popcount*1000),8.2);
+                        * for events between 20 and 100, use T distribution to calculate confidence intervals;
+                        * note LL and UL are calculated in step 4 above.
+                        
+                                redflag=put('-', $15.); 
+
                         end;
 
                         *  and normal approximation for more than 100 events. ;
+                        * which is also computed in step 4 above
                         
                         if count>100 then do;
-                                t1=(mean-(1.96*stderr)); 
-                                if (t1<0) then t1=0; 
-                                LL=put(t1, 8.2);
-                                UL=put((mean+(1.96*stderr)), 8.2);
-                                LL=compress(LL);
-                                UL=compress(UL);
+
                                 redflag=put('-', $15.); 
                         end;
@@ -246 +297 @@
 
                         if 20<=count<=100 then do; 
-                        * for events between 20 and 100, use Poisson to calculate confidence intervals;
-
-                                *mean=(rate*1000);
-                                t1= GAMINV(.025,count)/popcount*1000;
-                                if (t1<0) then t1=0;
-                                LL=put(t1, 8.2);
-                                UL=put(( GAMINV(.975,count)/popcount*1000),8.2);
+                        * for events between 20 and 100, use T distribution to calculate confidence intervals;
+                        * note LL and UL are calculated in step 4 above.
+                        
+                                redflag=put('-', $15.); 
+
                         end;
 
                         *  and normal approximation for more than 100 events. ;
+                        * which is also computed in step 4 above
                         
                         if count>100 then do;
-                                t1=(mean-(1.96*stderr)); 
-                                if (t1<0) then t1=0; 
-                                LL=put(t1, 8.2);
-                                UL=put((mean+(1.96*stderr)), 8.2);
-                                LL=compress(LL);
-                                UL=compress(UL);
+
                                 redflag=put('-', $15.); 
                         end;