I have a problem interpreting confidence interval for vaxera and vaxera2017. What does (0 .) Confidence interval mean? .Or am I doing something wrong to get that confidence interval
below is my data and code
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Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte agegp int year byte vt double time int bcd byte ipd double(vaxera postslope vaxera2017 postslope2017) 1 1999 2 1 381 4 0 0 0 0 1 2000 7 2 437 8 0 0 0 0 1 2001 0 3 461 0 0 0 0 0 1 2002 6 4 354 7 0 0 0 0 1 2003 4 5 295 5 0 0 0 0 1 2004 3 6 379 5 0 0 0 0 1 2005 2 7 412 2 0 0 0 0 1 2006 2 8 418 4 0 0 0 0 1 2007 2 9 383 3 0 0 0 0 1 2008 1 10 371 2 0 0 0 0 1 2009 0 11 375 0 0 0 0 0 1 2010 2 12 415 3 0 0 0 0 1 2011 0 13 398 1 . . . . 1 2012 0 14 318 0 1 1 0 0 1 2013 0 15 291 0 1 2 0 0 1 2014 0 16 396 0 1 3 0 0 1 2015 0 17 410 1 1 4 0 0 1 2016 0 18 436 0 1 5 0 0 1 2017 0 19 153 0 1 6 1 1 1 2018 1 20 294 1 1 7 1 2 1 2019 0 21 419 0 1 8 1 3 2 1999 4 1 1070 8 0 0 0 0 2 2000 8 2 1113 13 0 0 0 0 2 2001 15 3 1034 18 0 0 0 0 2 2002 6 4 586 6 0 0 0 0 2 2003 10 5 765 12 0 0 0 0 2 2004 9 6 789 13 0 0 0 0 2 2005 9 7 651 16 0 0 0 0 2 2006 3 8 763 6 0 0 0 0 2 2007 9 9 542 11 0 0 0 0 2 2008 5 10 496 6 0 0 0 0 2 2009 4 11 540 6 0 0 0 0 2 2010 7 12 386 9 0 0 0 0 2 2011 2 13 397 4 . . . . 2 2012 1 14 268 4 1 1 0 0 2 2013 0 15 176 1 1 2 0 0 2 2014 0 16 298 3 1 3 0 0 2 2015 1 17 257 4 1 4 0 0 2 2016 1 18 194 1 1 5 0 0 2 2017 0 19 67 0 1 6 1 1 2 2018 1 20 227 2 1 7 1 2 2 2019 0 21 226 1 1 8 1 3 3 1999 5 1 867 6 0 0 0 0 3 2000 10 2 826 15 0 0 0 0 3 2001 8 3 903 14 0 0 0 0 3 2002 8 4 600 9 0 0 0 0 3 2003 8 5 675 10 0 0 0 0 3 2004 4 6 642 6 0 0 0 0 3 2005 4 7 500 8 0 0 0 0 3 2006 4 8 502 7 0 0 0 0 3 2007 7 9 448 10 0 0 0 0 3 2008 4 10 363 4 0 0 0 0 3 2009 7 11 465 9 0 0 0 0 3 2010 8 12 339 8 0 0 0 0 3 2011 3 13 270 3 . . . . 3 2012 0 14 203 1 1 1 0 0 3 2013 0 15 148 1 1 2 0 0 3 2014 0 16 206 2 1 3 0 0 3 2015 0 17 226 1 1 4 0 0 3 2016 0 18 184 1 1 5 0 0 3 2017 0 19 62 1 1 6 1 1 3 2018 2 20 194 2 1 7 1 2 3 2019 0 21 230 2 1 8 1 3 4 1999 5 1 1172 6 0 0 0 0 4 2000 10 2 1106 11 0 0 0 0 4 2001 9 3 996 14 0 0 0 0 4 2002 4 4 746 6 0 0 0 0 4 2003 16 5 899 20 0 0 0 0 4 2004 9 6 714 12 0 0 0 0 4 2005 4 7 546 5 0 0 0 0 4 2006 5 8 586 6 0 0 0 0 4 2007 8 9 459 10 0 0 0 0 4 2008 6 10 457 7 0 0 0 0 4 2009 4 11 499 5 0 0 0 0 4 2010 22 12 508 26 0 0 0 0 4 2011 6 13 373 8 . . . . 4 2012 2 14 228 2 1 1 0 0 4 2013 0 15 190 2 1 2 0 0 4 2014 1 16 374 5 1 3 0 0 4 2015 1 17 335 3 1 4 0 0 4 2016 0 18 215 2 1 5 0 0 4 2017 0 19 83 1 1 6 1 1 4 2018 0 20 290 1 1 7 1 2 4 2019 1 21 247 3 1 8 1 3 5 1999 6 1 504 8 0 0 0 0 5 2000 12 2 482 15 0 0 0 0 5 2001 12 3 447 16 0 0 0 0 5 2002 10 4 294 12 0 0 0 0 5 2003 14 5 372 16 0 0 0 0 5 2004 20 6 285 24 0 0 0 0 5 2005 5 7 319 5 0 0 0 0 5 2006 2 8 307 3 0 0 0 0 5 2007 6 9 294 7 0 0 0 0 5 2008 3 10 257 3 0 0 0 0 5 2009 3 11 290 5 0 0 0 0 5 2010 12 12 349 13 0 0 0 0 5 2011 1 13 303 1 . . . . 5 2012 1 14 204 2 1 1 0 0 5 2013 2 15 213 4 1 2 0 0 5 2014 3 16 404 7 1 3 0 0 end label values agegp acat label def acat 1 "<2m", modify label def acat 2 "2-11m", modify label def acat 3 "12-23m", modify label def acat 4 "24-59m", modify label def acat 5 "5-14y", modify
use cleaned_datafiles/final_grouped_data_censoredd,clear
keep if agegp==1
tsset time
gen bcdnopnm =bcd-ipd
gen log_ipd = log(vt+1)
gen log_other_bld_cul = log(bcdnopnm)
**testing common trend(Common trend assumption met)
glm vt time if vaxera==0, link(log) family(nbinomial) exp(bcdnopnm) eform
**Testing interaction(interraction not significant)
glm vt vaxera postslope vaxera2017 postslope2017, link(log) family(nbinomial) exp(bcdnopnm) eform
***Unadjusted model
glm vt vaxera, link(log) family(nbinomial) exp(midyrpop) eform
**Final model
glm vt vaxera vaxera2017 , link(log) family(nbinomial) exp(bcdnopnm) eform
0 Response to Confidence interval
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