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st: groups by two or more variables
Hi,
Is there a way to create groups (say 25 groups) by two variables? Here X and
Y,
Year id X Y
986 6215 1 .645
1986 1781 1 .778
1986 2774 1 .819
1986 6354 1 .921
1986 6297 1 1.154
1986 6852 1 1.218
1986 6390 1 1.994
1986 7241 1 2.226
1986 6328 1 2.276
1986 4846 1 2.432
1986 6779 1 2.531
1986 67 1 2.97
1986 5452 1 3.422
1986 232 1 3.699
1986 6680 1 3.816
1986 6803 1 8.242
1986 6748 2 .8505
1986 7420 2 .965
1986 6003 2 1.0065
1986 1134 2 1.0105
1986 5138 2 1.1095
1986 3932 2 1.1635
1986 6280 2 1.237
1986 2575 2 1.993
1986 6811 2 2.411
1986 2101 2 2.539
1986 4658 2 2.6265
1986 449 2 5.7535
1986 863 3 .7213333
1986 6398 3 .7516667
1986 4330 3 .8473334
1986 6751 3 .8583333
1986 3911 3 .8786666
1986 1393 3 .9943333
1986 2791 3 1.095667
1986 1020 3 1.235667
1986 7424 3 1.242667
1986 6254 3 1.248667
1986 4196 3 1.988667
1986 3176 3 2.129
1986 6953 3 6.286667
1986 2223 4 .65475
1986 6220 4 .72
1986 1050 4 .7285
1986 3316 4 .79275
1986 1227 4 .81325
1986 1927 4 .9325
1986 6893 4 1.4805
1986 1992 4 4.23975
1986 1725 5 .826
1986 6216 5 .9128
1986 581 5 .9368
1986 3663 5 1.0186
1986 6204 5 1.0572
1986 6377 5 1.1318
1986 6845 5 2.5192
1986 541 6 .636
1986 1769 6 .8213333
1986 7253 6 .9143333
1986 7079 6 1.001833
1986 2961 6 1.006167
1986 650 6 1.469333
1986 4557 6 2.343167
1986 4526 7 .8422857
1986 7219 7 .8551429
1986 3601 7 .9331428
1986 2049 7 .9377143
1986 3423 7 1.194857
1986 6371 7 1.230286
1986 3296 7 1.416714
1986 4029 8 .8565
1986 2833 8 1.04075
1986 6051 8 1.057875
1986 6889 8 1.111875
1986 2520 8 1.248125
1986 2825 8 1.493875
1986 2834 9 .8953333
1986 6209 9 .9325555
1986 5355 9 1.174444
1986 2838 9 1.243778
1986 7220 10 .6192
1986 1213 10 1.0426
1986 3200 10 1.2048
1986 6917 10 1.2685
1986 1856 10 1.3986
1986 2273 10 1.5251
1986 780 11 .8487273
1986 5530 11 .9084545
1986 3229 11 1.124909
1986 1422 11 1.433091
1986 7289 11 1.535455
1986 3011 12 .6015833
1986 2932 13 .6307692
1986 5696 13 .6867692
1986 1895 13 .7826923
1986 2764 13 .9275385
1986 6733 14 .9395714
1986 634 14 1.027643
1986 6383 14 1.160286
1986 6926 14 1.282857
1986 6691 14 2.482214
1986 7280 15 .5949333
1986 1030 15 .8263333
1986 7260 15 .9454
1986 260 15 1.1282
1986 447 15 1.259267
1986 937 15 2.193
1986 7174 15 2.418334
1986 3606 16 .981
1986 1090 17 .6685294
1986 520 17 .7210588
1986 809 17 1.131529
1986 3306 17 1.180471
1986 5035 18 .6151111
1986 2829 18 .8278334
1986 5686 19 .6185263
1986 1404 19 .6494737
1986 6772 19 .8598947
1986 2650 20 1.03155
1986 6912 20 1.26795
1986 2258 20 1.2814
1986 6200 21 .8549524
1986 4021 21 1.135333
1986 1857 21 1.243905
1986 2221 22 .6185909
1986 1961 22 .7391818
1986 5162 22 .7798182
1986 6759 22 .8664545
1986 3662 24 .7367499
1986 3234 24 1.114333
1986 2756 24 1.138667
1986 7288 25 .67036
1986 3154 25 1.00056
1986 3266 27 .8845555
1986 3373 27 1.479741
1986 7323 27 1.545296
1986 6925 28 .9295357
1986 4639 28 1.24175
1986 3753 29 .9623449
1986 1827 29 1.121621
1986 1736 29 1.131655
1986 2922 29 1.158
1986 1233 30 1.248
1986 5500 31 .6467742
1986 1688 31 1.219968
1986 5760 31 1.53029
1986 1189 32 .7494687
1986 5524 32 1.145594
1986 784 33 .9015151
1986 614 33 1.039606
1986 4243 33 1.14003
1986 2165 34 1.114
1986 5505 35 .7846286
1986 3337 40 .9875
1986 94 41 1.221537
1986 1776 42 .7180238
1986 2361 42 4.724024
1986 3052 43 1.23414
1986 7043 47 1.234277
1986 6530 49 1.226735
1986 2810 51 .8077059
1986 1777 52 1.259385
1986 3785 53 1.101679
1986 2123 54 1.119148
1986 757 54 4.539814
1986 5087 56 1.283143
1986 844 59 .7798983
1986 4599 60 1.036933
1986 6579 60 3.429917
1986 1831 61 1.221049
1986 6766 62 1.260548
1986 5252 63 1.216698
1986 2498 64 .8532969
1986 6250 68 .7892647
1986 1155 69 1.269333
1986 3261 70 .6732715
1986 3201 70 1.1873
1986 1039 75 .9410933
1986 426 77 1.192559
1986 1950 77 1.516922
1986 9 78 1.25
1986 5294 79 .8405949
1986 5098 80 1.213163
1986 390 81 .8158889
1986 1491 81 1.023877
1986 3649 82 .5865853
1986 4915 83 1.280253
1986 2666 87 .6646092
1986 3003 90 1.021233
1986 1965 93 1.157559
1986 3805 93 1.224559
1986 5263 96 2.172917
1986 4193 105 1.084371
1986 3393 107 .7216729
1986 3491 107 1.164075
1986 4614 108 1.043407
1986 4586 110 1.181691
1986 158 111 1.172018
1986 2350 119 .7596639
1986 4718 120 .8131583
1986 3595 126 1.22446
1986 3007 129 1.210829
1986 5253 133 1.24279
1986 2301 133 1.255195
1986 7232 139 .9599856
1986 3614 147 .6333333
1986 1450 150 .6472933
1986 2741 156 1.150083
1986 7011 160 .9860312
1986 5305 163 1.184429
1986 4572 166 1.283777
1986 2365 166 5.42053
1986 1019 170 .6333706
1986 5216 181 .807453
1986 657 182 1.149483
1986 1971 184 .6699783
1986 3489 184 1.269315
1986 4546 192 1.194411
1986 4440 198 .7549646
1986 6653 208 1.27563
1986 3843 217 .9751152
1986 5255 220 1.002273
1986 3402 226 .5967788
1986 2477 238 .6786134
1986 3113 244 .5905738
1986 6047 247 .9202713
1986 2687 257 1.103988
1986 4552 261 1.132889
1986 1555 263 .7302281
1986 5405 275 .6592727
1986 674 283 .7971731
1986 5689 290 1.192352
1986 4560 292 1.203819
1986 6528 297 .7919192
1986 6726 297 1.456229
1986 1397 332 .7204819
1986 6654 334 1.119761
1986 7198 339 .6253687
1986 1755 343 1.214857
1986 97 343 1.284787
1986 5077 348 1.14381
1986 4744 368 1.4875
1986 938 389 .8467866
1986 4256 453 .6399558
1986 798 462 .5989178
1986 424 487 .826078
1986 2407 502 .848008
1986 3250 540 1.190185
1986 1825 568 .7835158
1986 2304 622 1.020257
1986 2998 657 .8304414
1986 3687 754 1.168568
1986 1313 949 1.221496
1986 2303 1144 .7687937
1986 6792 1175 1.009532
1986 4345 1574 .9343075
1986 98 1835 .7093188
1986 5290 2173 1.52416
1986 3701 2497 1.189828
1986 2227 3076 .6346879
1986 433 3271 .9935799
1986 753 4617 .7927225
1986 2675 4930 .7089249
1986 817 10212 .962593
I can create, quintiles of X and then for each of those create quintiles of
Y giving me 25 groups.
Using the following code
sort X
xtile mc=X,nq(5)
gen bm=.
levels mc, local(levels)
foreach i of local levels {
xtile bm_`i'=Y if mc==`i',nq(5)
replace bm=bm_`i' if mc==`i'
drop bm_`i'
}
tostring bm mc,replace
gen a=mc+bm
I want to see how this differs from a grouping based on a double sort of X
and Y.
So I need to do
sort x y
gen b=_n
gen group=floor(_n/10) * as in this case I have 264 observations)
is this the best approach?
rajesh
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