I would like to Test for differences in Medians for Multiple Variables Using qreg following the Stata Journal
HTML Code:
https://journals.sagepub.com/doi/pdf/10.1177/1536867X1201200202
Code:
qreg var1 class qreg var2 class qreg var3 class qreg var4 class
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double(var1 var2 var3 var4 class) 2.1709347229330476 .02042863528691251 .03228491681068315 6.344270516206654 1 5.487542064826069 .12843769095325996 .04757251167276653 6.154184831332533 1 2.403442868218309 .14004722153361354 .056244318978395644 6.982910060182892 1 1.1505027133742167 .11100197329982031 .004023767790014441 6.811365516638235 1 1.8804746970472777 .5373991437510292 .007095957516877986 9.874810261649259 1 1.9808765550239236 .3227327984439582 .021833211767566252 9.931394505789136 1 2.676107983414312 .2086538813493268 .07895762414439786 6.142981046239942 1 5.0250382942155865 .5440525877207101 .025750244090855447 5.636962241280868 0 4.258091546463471 .012181876701455542 .04470620519153116 6.660379227959387 1 2.197711032881432 0 .03437963510075126 4.4299473733834605 0 2.2245278845356267 .4394672805861094 .009428517082833212 5.723343242641416 1 1.1452441380506346 .005852152919964551 .0037893836139718242 11.088995933771097 1 .9484033697297157 .3734964247700097 .002009329861113992 7.095376932085215 1 1.1523751483206472 .2830885583049549 .014212063384959249 5.654406639014709 1 1.7533311612460127 .19266922499285918 .06038927853563682 7.63872652475961 1 .8706634694165418 .27225441581137516 .013483301895410065 7.3137409182571105 1 1.079994695584802 .24342634444177425 .00556080453072516 8.201428740938756 1 .9901501157807883 .200563603986151 .008008362894517725 6.203767551444203 1 1.3157547495682214 .013003901170351105 .11967674566421503 8.84246002419529 1 1.6125047223917022 .27092330708216894 .00022581646766590453 10.475257746929474 1 1.6695885509839 .7825286415711947 -.0016366612111292963 8.494743062578646 0 .8480628518530803 .3766737329713641 -.0002713747199372005 7.579527636994385 1 1.060821685855263 .2603442745643109 -.002459104030792259 9.143559338285831 1 1.6878696906442758 .11737663668433701 .0026116483332574844 7.910486424877584 1 3.968033586295519 .09784727102453503 .04043281225865062 7.8916183004611 1 .899243711630933 .12953298510293923 .002730703847420142 8.836453142906317 1 1.876879945068383 .2996552112194602 .006820006046659643 8.30061876606964 0 .9541869853059908 .3654661990765307 .017404474266007573 7.69546963611513 1 1.9644481201108408 .4032161241201265 .005893921591571983 11.974259250751283 0 2.5286603845167903 .3319836814821631 .012760344774700163 10.392128915166236 1 2.5399946760599135 .28070659154350697 .014606202798280617 6.371492181952594 0 1.9045555011585498 .2964226277064348 .03337520020575096 8.209402284791736 1 5.716134885512472 .5292907790381521 .008094833449250688 8.67395024313201 0 1.3615053404450799 .14013686402856293 .0557818383280838 11.487299917331256 1 2.4918920664014497 0 .022622035593839667 5.8137662863912745 1 4.115151363312894 .41287287656029065 .0038089010156910734 7.650706871093464 0 2.355544245111873 .18922108333108298 .0066966541804420205 7.86064405705401 0 1.1459177647714638 .3806578806414909 .011546484840845521 7.993001640282866 1 1.4456867284194304 .2235793293343836 .0307410848329395 6.388823556055131 1 2.433206439905795 .05182226940660904 .005467731741770416 8.736676452032238 1 .6718319519007932 .24684993964632423 -.0034781785701610136 8.62690498651182 0 1.610265383568393 .003758584550491892 .0015988813762135522 8.218744836646748 0 1.5904666612063105 .08420437504195837 .004750224395124635 8.339667396550764 1 .4844194771165337 .19147015156146804 .008096030121903125 8.126672457793893 1 1.1255137911908935 .013977875086425444 -.022882576630560036 5.852547247921313 0 1.0980541357873876 .23833167825223436 .0021414722790804503 9.602645938552133 1 1.459342862276669 .2960699771294345 .026362620968550576 8.654420620275989 1 3.7872993641364756 .16344200892632452 .03434962682508268 6.424757186209322 1 1.3330632839020906 .14922273950851017 .028375058135984177 5.3653356230988205 1 1.7050250470489474 .09482475476419729 .044931304649582844 8.317028590089064 1 1.4095675648788928 .45225421663566984 .012633874174308985 9.654641503869545 1 .9817325091888597 .19951911856495427 .01903986539661863 6.826789228492126 0 4.749956883277682 .004365141127600385 .03350505532830546 8.57455905040462 1 2.6315519937451133 .24769642069198225 .04563033716614323 8.256789004740584 1 1.2951633934280147 .40049463644969263 .008107996872041815 6.28326437993576 1 1.6885666182075358 .12606567517413872 .007133636339187263 6.390119854398666 1 2.0852919852933036 .22075020161884867 .03615227896612162 8.04582799565937 1 .6189007671401604 .25361495023248226 .010725521502892112 7.872453625672574 0 1.5426325594770125 .2503213115847204 .038414029355626496 6.398403568472147 1 5.431799918831169 .48254364089775564 .03834164588528678 6.465522446681758 1 .6169221507832088 .09853527536057495 -.0068559833290489135 5.904451351934881 1 1.3892754575052342 .054018197650424475 .02138990983282448 7.747180085196543 1 3.208024624600127 .2938049183043822 -.018247490676978 7.8478625324739415 1 2.0495010093948625 .07491891129600903 .028160696657735153 5.4289595895385325 1 1.914610189433304 .12734084304731733 .03212300106711626 7.359841852124484 0 .4680346209512774 .07488053707720517 .0033831925393684814 8.738226678109067 1 1.5331495506412196 .2399151993404393 .02296684529768565 9.739909238559308 1 2.4155976127480647 .1974669905582754 .04859411600264234 8.57590766064048 1 1.3535190448409071 .5582551101016601 -.005989655296997654 9.011132073356997 1 1.8093710795578795 .3263061983574228 .02702264160363464 6.177338121345474 1 2.413543812058275 .13404023535930262 .007393056878498134 9.294058900151573 1 1.7598221676427495 .35767105564133356 .011749799851318124 6.3289790974743 1 1.9380582068072627 .24758035817844862 .03609937184292087 7.932295030766125 0 2.0306460746550394 .24806585552336896 .021115980979310157 6.4785541880673865 1 1.8385283854866579 .19986105409416743 .020652414185113842 10.363061986291324 1 1.9736462512097805 .06855061601161756 .024047875579706748 6.750961108209461 0 1.9769853417901335 .33724378397180416 .017118646198720125 7.777863842906347 1 1.8545938219946896 .30055710669517777 .018918646200314113 7.636383979077606 1 2.886666087988723 .15277429315835184 .03533725755090225 10.855454260862754 1 1.3807206988594998 .616143277023171 .003723889966898756 5.639606554437637 1 2.2361776526107477 .26794909161566116 .012921402895171477 7.630267068171986 1 9.28029906542056 .27524229074889867 .04070484581497797 8.644002038279933 1 .8217743575613246 .30930619871638637 .007741141789399162 5.845432488574447 1 1.3653890875928012 .22438623490829931 .01337300005543486 7.03656089770649 0 2.800319755600815 .3067567966466924 -.00008855565723056941 10.430521115146327 1 3.927241192562631 0 .05982923895641445 8.717433576126178 1 .5205014326016568 .17731842326756325 .0007743689109328184 8.6229545667191 0 .7988620988725066 .18910471323051906 .002006304018415759 5.249142878535657 0 1.1528772598589017 .27211150188875866 .013282133925851286 8.443672585190909 1 1.0824540711537936 .31280606062952193 .01893637035804013 7.857182870229327 1 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0 Response to Test for differences in Medians for Multiple Variables Using qreg
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