计算具有重复 ID 的观察结果
Counting observations with duplicate ID's
我有一个要从宽格式转换为长格式的数据集。
目前我对每位患者进行 1 次观察，每位患者最多可以有 5 个动脉瘤，目前以宽格式记录。
我正在尝试重新安排此数据集，以便我对每个动脉瘤进行一次观察。我已经成功地做到了，但现在我需要在一个名为 aneurysmIdentifier.
的新变量中标记动脉瘤
Here是数据一瞥。您可以看到，当患者有 4 个动脉瘤时，我如何成功创建 4 个相应的观察结果，但是这些是通过 expand 函数创建的重复项。
我被困在下一点，如前所述，它正在创建一个新变量 aneurysmIdentifier，如果只有一个特定 record_id 的副本，则为 1，如果为 1 和 2有两个副本，一直到 1-2-3-4-5。这将使我能够对我所说的动脉瘤 1、2、3、4 和 5 有一个参考点，这样我就可以继续重新安排数据以适应这样的情况。
我已经创建了 this sketch 希望展示我的意思。如您所见，它会计算重复项的数量，然后向前计数，直到最大值为 5。
任何人都可以在正确的方向上推动我实现这一目标吗？
数据示例：
* Example generated by -dataex-. To install: ssc install dataex
clear
input str32 record_id float aneurysmNumber
"007128de18ce5cb1635b8f27c5435ff3" 1
"00abd7bdb6283dd0ac6b97271608a122" 1
"0142103f84693c6eda416dfc55f65de1" 1
"0153826d93a58d7e1837bb98a3c21ba8" 1
"01c729ac4601e36f245fd817d8977917" 2
"01c729ac4601e36f245fd817d8977917" 2
"01dd90093fbf201a1f357e22eaff6b6a" 1
"0208e14dcabc43dd2b57e2e8b117de4d" 1
"0210f575075e5def7ffa77530ce17ef0" 1
"022cc7a9397e81cf58cd9111f9d1db0d" 1
"02afd543116a22fc7430620727b20bb5" 1
"0303ef0bd5d256cca1c836e2b70415ac" 2
"0303ef0bd5d256cca1c836e2b70415ac" 2
"041b2b0cac589d6e3b65bb924803cf1a" 1
"0536317a2bbb936e85c3eb8294b076da" 1
"06161d4668f217937cac0ac033d8d199" 1
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"07196414cd6bf89d94a33e149983d102" 1
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"07bef516d53279a3f5e477d56d552a2b" 1
"08678829b7e0ee6a01b17974b4d19cfa" 1
"08bb6c65e63c499ea19ac24d5113dd94" 1
"08f036417500c332efd555c76c4654a0" 1
"090c54d021b4b21c7243cec01efbeb91" 1
"09166bb44e4c5cdb8f40d402f706816e" 1
"0930159addcdc35e7dc18812522d4377" 1
"096844af91d2e266767775b0bee9105e" 1
"09884af1bb9d59803de0c74d6df57c23" 1
"09e03748da35e9d799dc5d8ddf1909b5" 1
"0a4ce4a7941ff6d1f5c217bf5a9a3bf9" 1
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a73c992955231650965ed87e3bd52f6" 1
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0af333ae400f75930125bb0585f0dcf5" 1
"0af73334d9d2166191f3385de48f15d2" 1
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b3e110c9765e14a5c41fadcc3cfc300" .
"0b6681f0f441e69c26106ab344ac0733" 1
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b92c26375117bf42945c04d8d6573d4" 2
"0b92c26375117bf42945c04d8d6573d4" 2
"0ba961f437f43105c357403c920bdef1" 1
"0bb601fabe1fdfa794a5272408997a2f" 1
"0c75b36e91363d596dc46bd563c3f5ef" 1
"0d461328a3bae7164ce7d3a10f366812" 1
"0d4cc4eb459301a804cbef22914f44a3" 1
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d513c74d667f55c8f4a9836c304149c" 1
"0da25de126bb3b3ee565eff8888004c2" 2
"0da25de126bb3b3ee565eff8888004c2" 2
"0db9ae1f2201577f431b7603d0819fa6" 1
"0dd8a681f6a5d4c888831a591e57a747" 1
"0e05d6958d878368b5fb831211fad6a1" 1
"0e3ff41e0e2b2cb5ec336fd0b04e5d44" 1
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f69f1f998984d37f133185179d63c60" 1
"1037032886a93e66406a4c910d1ef747" 2
"1037032886a93e66406a4c910d1ef747" 2
"1044b81b354b420e85ae835ea07de2d6" 1
"10620fc488346291281212a404681386" 1
"1074389c469944edf026d193a55b1148" 1
"1090d5a678119b03cddab609289a4d3c" 1
"111eebb45cef2211a2a2ff0219095e6a" 1
"11ddcbc8de8ef56cbc578fc81b602ffc" 1
"11f22488513cf717c333786c789b0289" 2
"11f22488513cf717c333786c789b0289" 2
"121552b22cee2a1eb4360b4d2534cd39" 1
"1251d707c5dc9243dc45d04beb7c3493" 1
"125689659bb3821fa81698dd72462773" 1
"127ba572433921c5bb408fc62eb9b5d7" 1
"129bea3f73e84e37d77d55fadfeb49dd" 1
"12e8dc6fb87822be26d6678cee9644f5" 1
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"13d2bc86f1a19ed2959cd7354bc92d1d" 1
"13db5ede38e2ae1da17884c9a18df202" 1
"13f946e50df8ad74d7cf9fa05b4ad05b" 1
"146c4b8be7996a9789873fe55a47ab41" 1
"147fadd87da13a0271225d944d2a5e98" 1
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14d1377f74a63ffa29db2d99e7f6a1ce" 1
"150017d944a87b4c61f90034380c0659" 1
"150f6ca1ea453260eabf3472d3ebcad1" 1
end
你可以去
bysort record_id: gen aneurysm_id = _n
但结果将是任意的，除非有一些其他信息（比如日期变量）为排序提供依据。假设有一个日期变量 date，它是数字且顺序良好。那么
bysort record_id (date) : gen aneurysm_id = _n
将是一个合适的修改。对于日期，如果注意到一天中的时间并且值得注意，也可以阅读日期时间。
我有一个要从宽格式转换为长格式的数据集。
目前我对每位患者进行 1 次观察，每位患者最多可以有 5 个动脉瘤，目前以宽格式记录。
我正在尝试重新安排此数据集，以便我对每个动脉瘤进行一次观察。我已经成功地做到了，但现在我需要在一个名为 aneurysmIdentifier.
Here是数据一瞥。您可以看到，当患者有 4 个动脉瘤时，我如何成功创建 4 个相应的观察结果，但是这些是通过 expand 函数创建的重复项。
我被困在下一点，如前所述，它正在创建一个新变量 aneurysmIdentifier，如果只有一个特定 record_id 的副本，则为 1，如果为 1 和 2有两个副本，一直到 1-2-3-4-5。这将使我能够对我所说的动脉瘤 1、2、3、4 和 5 有一个参考点，这样我就可以继续重新安排数据以适应这样的情况。
我已经创建了 this sketch 希望展示我的意思。如您所见，它会计算重复项的数量，然后向前计数，直到最大值为 5。
任何人都可以在正确的方向上推动我实现这一目标吗？
数据示例：
* Example generated by -dataex-. To install: ssc install dataex
clear
input str32 record_id float aneurysmNumber
"007128de18ce5cb1635b8f27c5435ff3" 1
"00abd7bdb6283dd0ac6b97271608a122" 1
"0142103f84693c6eda416dfc55f65de1" 1
"0153826d93a58d7e1837bb98a3c21ba8" 1
"01c729ac4601e36f245fd817d8977917" 2
"01c729ac4601e36f245fd817d8977917" 2
"01dd90093fbf201a1f357e22eaff6b6a" 1
"0208e14dcabc43dd2b57e2e8b117de4d" 1
"0210f575075e5def7ffa77530ce17ef0" 1
"022cc7a9397e81cf58cd9111f9d1db0d" 1
"02afd543116a22fc7430620727b20bb5" 1
"0303ef0bd5d256cca1c836e2b70415ac" 2
"0303ef0bd5d256cca1c836e2b70415ac" 2
"041b2b0cac589d6e3b65bb924803cf1a" 1
"0536317a2bbb936e85c3eb8294b076da" 1
"06161d4668f217937cac0ac033d8d199" 1
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"07196414cd6bf89d94a33e149983d102" 1
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"07bef516d53279a3f5e477d56d552a2b" 1
"08678829b7e0ee6a01b17974b4d19cfa" 1
"08bb6c65e63c499ea19ac24d5113dd94" 1
"08f036417500c332efd555c76c4654a0" 1
"090c54d021b4b21c7243cec01efbeb91" 1
"09166bb44e4c5cdb8f40d402f706816e" 1
"0930159addcdc35e7dc18812522d4377" 1
"096844af91d2e266767775b0bee9105e" 1
"09884af1bb9d59803de0c74d6df57c23" 1
"09e03748da35e9d799dc5d8ddf1909b5" 1
"0a4ce4a7941ff6d1f5c217bf5a9a3bf9" 1
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a73c992955231650965ed87e3bd52f6" 1
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0af333ae400f75930125bb0585f0dcf5" 1
"0af73334d9d2166191f3385de48f15d2" 1
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b3e110c9765e14a5c41fadcc3cfc300" .
"0b6681f0f441e69c26106ab344ac0733" 1
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b92c26375117bf42945c04d8d6573d4" 2
"0b92c26375117bf42945c04d8d6573d4" 2
"0ba961f437f43105c357403c920bdef1" 1
"0bb601fabe1fdfa794a5272408997a2f" 1
"0c75b36e91363d596dc46bd563c3f5ef" 1
"0d461328a3bae7164ce7d3a10f366812" 1
"0d4cc4eb459301a804cbef22914f44a3" 1
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d513c74d667f55c8f4a9836c304149c" 1
"0da25de126bb3b3ee565eff8888004c2" 2
"0da25de126bb3b3ee565eff8888004c2" 2
"0db9ae1f2201577f431b7603d0819fa6" 1
"0dd8a681f6a5d4c888831a591e57a747" 1
"0e05d6958d878368b5fb831211fad6a1" 1
"0e3ff41e0e2b2cb5ec336fd0b04e5d44" 1
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f69f1f998984d37f133185179d63c60" 1
"1037032886a93e66406a4c910d1ef747" 2
"1037032886a93e66406a4c910d1ef747" 2
"1044b81b354b420e85ae835ea07de2d6" 1
"10620fc488346291281212a404681386" 1
"1074389c469944edf026d193a55b1148" 1
"1090d5a678119b03cddab609289a4d3c" 1
"111eebb45cef2211a2a2ff0219095e6a" 1
"11ddcbc8de8ef56cbc578fc81b602ffc" 1
"11f22488513cf717c333786c789b0289" 2
"11f22488513cf717c333786c789b0289" 2
"121552b22cee2a1eb4360b4d2534cd39" 1
"1251d707c5dc9243dc45d04beb7c3493" 1
"125689659bb3821fa81698dd72462773" 1
"127ba572433921c5bb408fc62eb9b5d7" 1
"129bea3f73e84e37d77d55fadfeb49dd" 1
"12e8dc6fb87822be26d6678cee9644f5" 1
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"13d2bc86f1a19ed2959cd7354bc92d1d" 1
"13db5ede38e2ae1da17884c9a18df202" 1
"13f946e50df8ad74d7cf9fa05b4ad05b" 1
"146c4b8be7996a9789873fe55a47ab41" 1
"147fadd87da13a0271225d944d2a5e98" 1
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14d1377f74a63ffa29db2d99e7f6a1ce" 1
"150017d944a87b4c61f90034380c0659" 1
"150f6ca1ea453260eabf3472d3ebcad1" 1
end
你可以去
bysort record_id: gen aneurysm_id = _n
但结果将是任意的，除非有一些其他信息（比如日期变量）为排序提供依据。假设有一个日期变量 date，它是数字且顺序良好。那么
bysort record_id (date) : gen aneurysm_id = _n
将是一个合适的修改。对于日期，如果注意到一天中的时间并且值得注意，也可以阅读日期时间。