Hello everybody,
I have a hospital dataset (master.dta) containing information about surgeries performed in separate years. I would like to merge additional information about the cancer certification status of each hospital (using.dta). The datasets contains two differen variables for the geographical information of each hospital: ZIP codes (kh_plz) and municipality keys (hosp_AGS). I want to perform a hierarchical merge. First, I want to merge the data using the hospital zip code (kh_plz) information. For all unsuccessful mergers (_merge = 2), I would like to merge the data using the municipality keys (hosp_AGS). As there is no if condition for merging in Stata, could you suggest a workaround? Please note that the data i present is only a small snippet of the original file, so the results won't make to much sense....
Kindly,
Fred
Master File
------------------ copy up to and including the previous line ------------------
Listed 39 out of 39 observations
Using-File
----------------------- copy starting from the next line -----------------------
I have a hospital dataset (master.dta) containing information about surgeries performed in separate years. I would like to merge additional information about the cancer certification status of each hospital (using.dta). The datasets contains two differen variables for the geographical information of each hospital: ZIP codes (kh_plz) and municipality keys (hosp_AGS). I want to perform a hierarchical merge. First, I want to merge the data using the hospital zip code (kh_plz) information. For all unsuccessful mergers (_merge = 2), I would like to merge the data using the municipality keys (hosp_AGS). As there is no if condition for merging in Stata, could you suggest a workaround? Please note that the data i present is only a small snippet of the original file, so the results won't make to much sense....
Kindly,
Fred
Code:
use master.dta, clear // Upload Data merge m:1 kh_plz surgery year using "using.dta" // m:1 merge with using data gen DKG_Zentrum = 1 if _merge==3 // Generate a variable for a certified hospital if merging was successful merge m:1 hosp_AGS surgery year using "using.dta" if _merge==2 // How do can I make this word
Master File
Code:
* Master File * Example generated by -dataex-. For more info, type help dataex clear input long(kh_plz hosp_AGS) float(surgery year) 44649 2112000 2 2020 14165 9170147 2 2020 23562 5156016 4 2012 23562 5057119 4 2014 32756 3115072 1 2017 32756 5013020 1 2013 32756 4371000 1 2012 32756 11189016 1 2013 23562 5661012 4 2013 25746 9111 4 2018 25746 12116032 4 2013 25746 3226000 4 2019 25746 5462070 4 2018 25746 2712001 4 2012 25746 9662000 4 2018 32756 11152000 1 2011 32756 11061000 1 2014 25746 6225032 4 2020 23730 5359155 4 2019 23730 12211000 4 2017 23730 13074003 4 2017 23730 55002 4 2013 23730 9403000 4 2014 23730 7656000 4 2013 40489 5401022 5 2011 40489 8115050 5 2011 40489 14752000 5 2011 40489 9303000 5 2013 28205 14015000 1 2011 32756 15091000 1 2017 21339 5072081 4 2011 40489 8313000 5 2013 40489 3004006 5 2015 63755 14271002 5 2020 28209 16303045 4 2011 28209 6130000 4 2013 28209 9434000 4 2011 28209 8363008 4 2017 28209 8324028 4 2020 end label values surgery surgery label def surgery 1 "Pancreas", modify label def surgery 2 "Gastric", modify label def surgery 4 "Colon/Rectal", modify label def surgery 5 "Lung", modify
Code:
* Example generated by -dataex-. For more info, type help dataex clear input long(kh_plz hosp_AGS) float(surgery year) 44649 2112000 2 2020 14165 9170147 2 2020 23562 5156016 4 2012 23562 5057119 4 2014 32756 3115072 1 2017 32756 5013020 1 2013 32756 4371000 1 2012 32756 11189016 1 2013 23562 5661012 4 2013 25746 9111 4 2018 25746 12116032 4 2013 25746 3226000 4 2019 25746 5462070 4 2018 25746 2712001 4 2012 25746 9662000 4 2018 32756 11152000 1 2011 32756 11061000 1 2014 25746 6225032 4 2020 23730 5359155 4 2019 23730 12211000 4 2017 23730 13074003 4 2017 23730 55002 4 2013 23730 9403000 4 2014 23730 7656000 4 2013 40489 5401022 5 2011 40489 8115050 5 2011 40489 14752000 5 2011 40489 9303000 5 2013 28205 14015000 1 2011 32756 15091000 1 2017 21339 5072081 4 2011 40489 8313000 5 2013 40489 3004006 5 2015 63755 14271002 5 2020 28209 16303045 4 2011 28209 6130000 4 2013 28209 9434000 4 2011 28209 8363008 4 2017 28209 8324028 4 2020 end label values surgery surgery label def surgery 1 "Pancreas", modify label def surgery 2 "Gastric", modify label def surgery 4 "Colon/Rectal", modify label def surgery 5 "Lung", modify
Listed 39 out of 39 observations
Using-File
----------------------- copy starting from the next line -----------------------
Code:
* Using-File * Example generated by -dataex-. For more info, type help dataex clear input long(kh_plz hosp_AGS) float(surgery year dkg_certification_date) 24939 1001000 4 2013 19391 24105 1002000 1 2012 19247 24105 1002000 2 2020 21943 24105 1002000 4 2012 19247 24105 1002000 5 2019 21613 24105 1002000 6 2012 19311 24116 1002000 1 2020 21937 24116 1002000 4 2014 19960 25105 1002000 7 2018 21213 23560 1003000 4 2015 20388 23560 1003000 6 2016 20728 23562 1003000 1 2014 19852 23562 1003000 2 2019 21880 23562 1003000 4 2014 19852 24534 1004000 4 2016 20485 25746 1051044 4 2013 19516 23730 1055032 4 2021 22475 25421 1056039 4 2009 18074 24768 1058135 4 2012 19054 24768 1058135 6 2011 18722 25524 1061046 4 2012 19247 22927 1062023 5 2012 19179 21465 1062060 1 2020 22034 21465 1062060 4 2020 22034 20246 2000000 1 2021 22465 20246 2000000 2 2021 22465 20246 2000000 6 2008 17570 20251 2000000 4 2014 20013 20259 2000000 4 2007 17372 22297 2000000 4 2021 22516 22307 2000000 1 2010 18610 22307 2000000 4 2009 18153 38124 3101000 4 2016 20629 38126 3101000 1 2016 20489 38126 3101000 3 2019 21600 38126 3101000 4 2014 19940 38126 3101000 5 2018 21228 38126 3101000 6 2011 18983 38440 3103000 4 2016 20597 38440 3103000 6 2010 18613 38518 3151009 4 2008 17749 38302 3158037 4 2014 19927 37075 3159016 1 2018 21263 37075 3159016 4 2016 20796 37075 3159016 5 2015 20128 37075 3159016 6 2018 21259 30169 3241001 6 2009 18001 30171 3241001 4 2012 19281 30459 3241001 1 2016 20656 30459 3241001 4 2011 18794 30459 3241001 5 2010 18379 30459 3241001 6 2011 18752 30559 3241001 4 2008 17883 30625 3241001 1 2018 21208 30625 3241001 2 2019 21593 30625 3241001 3 2018 21208 30625 3241001 4 2019 21593 30625 3241001 5 2021 22308 30625 3241001 6 2012 19058 30625 3241001 7 2017 20844 30938 3241004 6 2011 18759 30989 3241006 1 2014 20027 30989 3241006 4 2011 18871 31134 3254021 1 2020 22198 31134 3254021 4 2009 18203 31135 3254021 1 2013 19553 31135 3254021 4 2007 17455 29223 3351006 1 2016 20805 29223 3351006 4 2013 19372 21244 3353005 4 2010 18394 21423 3353040 1 2021 22545 21423 3353040 4 2012 19157 21339 3355022 1 2014 19822 21339 3355022 4 2010 18470 21339 3355022 6 2012 19066 27356 3357039 3 2016 20629 27356 3357039 4 2011 18728 21682 3359038 1 2016 20730 21682 3359038 4 2007 17381 26121 3403000 1 2011 18842 26121 3403000 3 2018 21462 26121 3403000 4 2011 18842 26121 3403000 5 2011 18675 26133 3403000 6 2009 18144 49074 3404000 1 2020 22008 49074 3404000 4 2010 18333 49076 3404000 1 2012 19219 49076 3404000 4 2011 18744 26655 3451007 4 2007 17188 26655 3451007 6 2014 19940 49808 3454032 4 2015 20118 49124 3459019 4 2015 20165 49179 3459029 5 2011 18735 49377 3460009 4 2010 18493 28205 4011000 1 2014 19964 28205 4011000 4 2014 19964 28205 4011000 6 2012 19109 28239 4011000 4 2008 17713 28325 4011000 5 2009 18050 40217 5111000 1 2012 19064 end format %td dkg_certification_date label values surgery surgery label def surgery 1 "Pancreas", modify label def surgery 2 "Gastric", modify label def surgery 3 "Eosophageal", modify label def surgery 4 "Kolorektal", modify label def surgery 5 "Lung", modify label def surgery 6 "Prostata", modify label def surgery 7 "Leber", modify
Comment