Changeset 20026 in main
 Timestamp:
 03/13/20 09:50:45 (3 weeks ago)
 File:

 1 edited
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adopters/mt/trunk/src/main/backend_qModules/birth23/MT_Average_data_frame.def
r19929 r20026 264 264 end; 265 265 266 if 20<=count<=100 then do; 267 * for events between 20 and 100, use T distribution to calculate confidence intervals; 268 * note LL and UL are calculated in step 4 above. 269 266 * for events >= 20 use binomial exact confidence intervals; 267 268 if count >= 20, then do; 269 LL=put(t1, 8.2); 270 LL=(1 – betainv (.975, popcount – count – 1, count))*100); 271 UL=((1 – betainv (.025, popcount – count, count + 1))*100); 272 LL=compress(LL); 273 UL=compress(UL); 270 274 redflag=put('', $15.); 271 272 end; 273 274 * and normal approximation for more than 100 events. ; 275 * which is also computed in step 4 above 276 277 if count>100 then do; 278 279 redflag=put('', $15.); 280 end; 275 end; 276 281 277 end; 282 278 … … 296 292 * report rate and n if popcount <300 and count >= 20 events. ; 297 293 298 if 20<=count<=100 then do; 299 * for events between 20 and 100, use T distribution to calculate confidence intervals; 300 * note LL and UL are calculated in step 4 above. 301 302 redflag=put('', $15.); 303 304 end; 305 306 * and normal approximation for more than 100 events. ; 307 * which is also computed in step 4 above 308 309 if count>100 then do; 310 294 * for events >= 20 use binomial exact confidence intervals; 295 296 if count >= 20, then do; 297 LL=put(t1, 8.2); 298 LL=(1 – betainv (.975, popcount – count – 1, count))*100); 299 UL=((1 – betainv (.025, popcount – count, count + 1))*100); 300 LL=compress(LL); 301 UL=compress(UL); 311 302 redflag=put('', $15.); 312 303 end;
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