merge m:m vs joinby

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之前一直对merge m:m不感冒，直到最近才发现它的好处。

废话少说，上log
set obs 300
egen id=seq()
gen firm=1
save "firmid"
clear

set obs 10000
egen id=seq()
replace id=int(id/100) if id>100*there will be firm id greater than 100
gen employ=id+100
save "employ"

*i plan to assign each employ value in eploy.dta to firid.dta
use firmid.dta
sort id
merge m:m id using employment
*in this case, all firm id are kept

clear
use firmid.dta
joinby id using employ.dta
*in this case, only id <=100 are kept.



唉，怪自己不认真那

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关键词：joinby Merge join employment replace employment replace

感谢分享！

学习了

学习了

learning.

这是一种什么学习精神？joinby有选项

joinby id using employ.dta, unmatched(master)

楼主这种情况下不会报错是因为只有一个variable id
如果你做出两个 id1 和 id2
情况会大不一样
实际数据操作中很少有这么简单的merge

楼主 您的code有小问题哦
merge m:m id using employment
应该是merge m:m id using employ

楼主的操作有问题啊。看看Stata自己的解释吧：
“m:m specifies a many-to-many merge and is a bad idea. In an m:m merge, observations are matched
within equal values of the key variable(s), with the first observation being matched to the first; the
second, to the second; and so on. If the master and using have an unequal number of observations
within the group, then the last observation of the shorter group is used repeatedly to match with
subsequent observations of the longer group. Thus m:m merges are dependent on the current sort
order—something which should never happen.
Because m:m merges are such a bad idea, we are not going to show you an example. If you think
that you need an m:m merge, then you probably need to work with your data so that you can use a
1:m or m:1 merge.”

说的很清楚，merge m:m 是要避免使用的

xingxf 发表于 2014-5-13 06:37
楼主的操作有问题啊。看看Stata自己的解释吧：
“m:m specifies a many-to-many merge and is a bad idea. ...

我在进行merge的时候也出现了这个问题，用来合并的关键变量在两个文件中都有重复，成了多对多合并了，请问这种情况下一定要修改一下数据吗？