Question about Muti Variable ttest

[Cristiana LI]

Hi all!

I need to do a t-test on multiple variables. What code should I use?

How can I get the result like the pic shows.

Please anyone can help with this? Many thanks！

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* Example generated by -dataex-. For more info, type help dataex
clear
input long rdexp float(beta fret3 ret3 earns learns fearns cap lnsize bm rdint leverage roa rdvalue cvrd cvearn pastbeat zerobeat scapex srdexp rdcap imr GAAP IFRS)
    713    .418102    .4536135     .364551   .074198015   .05327313    .06973619 0 11.217332   .483678   .014047047   .4103362    .10877103    24.61179  .9175383  -7.630903 0 0   .016274912  .009582174          0  .5269771 0 1
   2391   1.474711   .58762884   -.1779661    -.2156156  -.11714503    .19082895 0 10.477372   .716024    .05543962   .6965501    -.1774949   1.3637224 .25163928 -2.0041196 0 0    .04540461  .067346424          0  .7546901 0 1
   5120   .9822725   .00993244 -.028219305    .05497606   -.2201342    .11687117 1 10.775597 1.2755283   .070371374   .3264831   .032492403  -1.1122268  .4401271   2.504248 0 0   .011538703   .10702565   .1011236  .5534333 0 1
    400   .3893762  -.28670505   .13655774   .025731616  -.13192558    .06575857 0  12.40834  .8323973   .001323189    .483317   .020840226    58.62143  .8648361  -2.557064 0 0   .027773807 .0016337533          0  .6900436 0 1
    687  1.2834226    2.491282   -.8193405    -.5499432   .05401669  -.009035698 1  9.916059  2.078902   .008661849  1.2484324   -.11765327    -7.74309  .4508246  2.3340344 0 0    .06754555    .0339209   .1621951  .6783608 0 1
   9800   1.752383    1.342881   -.4429851    .17476575   .12416375     .1945534 0 13.403065 1.0688354   .005630566   1.459723    .06647515   -2.436952  .7092915    .858834 0 0    .08051006  .014802977          0  .6575058 0 1
    364   .6990359    .6678303  -.26461294     .1753247     .479021    .24531025 0  9.799127  5.990259  .0015443098     .83759   .013402403  -238.63637   .614997   2.838983 0 0    .15440115   .02020202          0 .52769494 0 1
      0  .15735136    .6683516   .25919378   .033057455 .0012510826     .0870946 1  9.941842  .6741892   .006648251  .52444506    .03216443      27.084 1.0404801  -3.748522 0 0   .001443557           0          1  .4564438 0 1
  59633   .9990183   -.5307411   .26132077   .011262766  .010611583   .003454627 0  14.41253 .09764275     .3075626  .09302824    .10552945    15.71286  .9422877   1.787983 0 0   .004872587   .03282501          0  .7914402 0 1
2698803   .4646168  .025683524    .2603489    .11333287   .07843001    .12029687 0 17.558645  .3028296     .0812997  1.5957406     .1441771    5.516864  .1811704   .5356439 0 0   .014496231   .06390702          0 1.2398056 0 1
   3781   .5943138   .26802492    .5121059    .06239832   .04851596    .08529458 1 12.019538  .4797248    .02474423  1.0968626    .06203129   10.077965 .27393657  1.2360245 0 0    .04983551  .022781774  .08472525  .9660462 0 1
  19600  1.0173645   -.0491307    .3350085    .05036056    .0516048     .0552131 0  14.98328 .10672458    .02086216  1.7382687     .1723257    66.01648  .4825507   .8930355 1 0    .01567741   .00609677          0 1.1241391 0 1
   2818  .02481674    .3952368  -.18865184    -.0509631 -.036603943    -.1029575 0 11.051303  .8607242    .04844422 .072297595   -.05521747    1.709112  .7208628  -.6606542 1 0 .00022213055    .0447117          0   .614703 0 1
    362  2.2113674    .6843086      .40766     .1081234    .1236909     .2479479 1  8.169903 2.8361166   .033071402   .4605788    .02610181   -7.969287  .4554689   .3965381 1 0    .02292669    .1024625   .2520661 .21041867 0 1
  99360   .4219855   .08734102    .5473706    .05351457   .03619909   .070506565 0 15.547856 .23937817   .036664926  1.0022956    .11165015   23.644855  .3715401   .4909446 0 0    .03605441  .017573712          0 1.1048564 0 1
    147  -.0802944   .03030276   .13793145  -.017658731 -.028670635  .0008928571 0  9.218308  .3375992   .020496374  1.1075522   -.02481874   21.196825  .2515319  1.0231887 0 0   .014186508  .014583333          0  .8036731 0 1
    404   .6852044    .0076322  -.24263693   -.17170323  .017864333    .05612914 0 11.667473 1.0591023  .0016257153  1.0103874   -.08064192   -4.544137   .614997   2.838983 0 0    .03924156 .0034614825          0  .7187973 0 1
  17000    .591129    .4494443    .1619638    .05989315    .0513505     .0612171 0 17.272558 .16533662  .0008826125   2.672259    .09864493    882.6053  .7987891   .3924578 0 0   .013208016 .0005358861          0 1.1597694 0 1
   1432   .4685867   .23168376   .30246815    .06735212  .031765718     .0983577 1 10.819598  .7029265    .02289515    .779909    .05383238   4.6351438  .9833779   .9105949 0 0   .010601908  .028645156          0  .6389568 0 1
   3027   .4446894  -.04150123   -.1037798    .05172852  .067716725  -.017242841 0  10.98497 .56389344    .06729059   .3525361    .06782412     4.57524  .4733404  1.9200794 1 0   .066801175   .05132161          0  .7710562 0 1
  19739   1.026432   .06152993   .12036803   .027331246   .01300334    .02715625 0  12.82515 .35839415    .09158482   .6190065    .04710315    5.856967  .4398406  .54125005 0 0   .005373637    .0531414          0  .6594313 0 1
  10200   1.244634   .18196715   .03725344 -.0033492015   .03753415   .062941894 0   13.6715 .13142729    .02035928  3.4024606  -.005788423    39.58305 .13036852   1.840894 0 1   .008777218   .01177995          0  .8540537 0 1
      0   .8777477  -.22068973 -.033334892   -.26230508   -.4239157   -.56950533 1  9.706012 1.8861476   .001878158  1.4418176   -.05695315   -79.49181  .7575938 -2.6995134 0 0    .04075292           0          1  .7070601 0 1
    104   .7186078   .09411765   -.5430108    -.2727781   -.6048071   -.06036892 1  7.489412 1.1095585    .04813315  .11989924   -.21952316     -.92891 .57082057  -.7588347 0 0     .0117384   .05813304  .02803738  .8509201 0 1
   2696   .9968019 -.063451774 -.024752475   .029134266   .01078279   .035355106 0  9.174195  .3384137     .2330164  2.5447304    .02428695   1.0684862 .30256715  -1.932036 0 0    .01410057   .27952307          0  .8809537 0 1
    394   .8190526   .23744515   .53863466     .2015912   .23119223     .1831052 0  9.053335   .932725    .04235193  .16695936    .18520907    .8805513  .3828929  -2.591862 1 0    .01088101   .04609805          0 .31142995 0 1
      0  1.7915075    .5707337   -.6161519    .16246566   .29447407   .013814833 1  9.423676  2.545484    .07156539  .50783926    .04232882   -2.521418  .5655103  2.7374754 0 1    .05016965           0          1 .25111014 0 1
   7000  1.7571427   1.1772497  -.36477455    .03539279   .07362066    .03667315 1 13.904842 1.8670384   .005310168  1.0017145   .009470207    -43.0935  .6646563   .6116708 0 0     .0409715  .006401797   .6774194 .52343863 0 1
    864   .3774369  -.06477046    .2229455    .07435987    .0573483    .12942827 1  8.648572 1.1743248    .07946843   .6744325    .03781663   -.5152929  .3154444  1.5222405 0 0    .03384777    .1515258  .03030303 .58801013 0 1
   3703   .8098639     .422883   .24960615     .0435568   .03357071    .06046602 1 12.310473  .2463864    .06937451   .3579159     .1301866   16.584953 .46928585   .5854959 0 0   .011314857  .016679505  .28138947  .7187606 0 1
  28100  2.3819463    .4509649   .05122212    .08478254  -.21697037    .05615703 1 13.214873  .8038843    .03686747    .882513     .0560241   1.7019304  .6917405   9.865089 0 0    .02479661   .05123418  .08169935  .5009176 0 1
    500   1.385002  -.06164151    .5531704   -.01242133   -.1324942    .08556917 0 11.190735  .7563211   .003050641   1.990876  -.005491153   19.617777  .7224087   4.331229 0 0    .04968533   .00690074          0  .6116475 0 1
    133  1.2465625   .23476796 -.003901735    .04409335   .08405618    .07765386 0   9.17823  .6402313   .012429907   .7258065    .03990654    9.731844  .2515319  1.0231887 0 0    .04997935  .013733994          0  .7857031 0 1
  45200  1.0906333   -.4415684   -.1369402    .10866839   .07740416    .10223905 0  13.58388  .3817261    .07264545  1.0548216    .13854066    5.455384  .4612735   .7264649 0 0   .016010307   .05698157          0  .7595152 0 1
    391  1.0257378    .3460012    .5359969    .09359641   .07355811     .0878144 0 10.921324 2.2619796  .0015198278  1.0550536   .020134803   -91.53735   .614997   2.838983 0 0    .05671798  .007064903          0  .6644087 0 1
   1108   .9713376   .54303914  -.21672425    .05455968    .3935435    .09419204 0  9.638285 1.4319144   .021424703  1.3542587   .016184546   -3.180989  .2302805  1.3759422 0 0      .385894   .07222476          0  1.826868 0 1
  24300  1.1134785   .08458035 -.007532011    .02335521   .02632769   .019321127 1 13.755733 .14618237    .08195616  1.1532316    .07419899   14.159754  .3663986  1.8752563 1 0   .009129764   .02579689          0  .6905732 0 1
   3100  1.2776462   .08115449    .9185406    .05179175 -.004932547    .17263916 1  11.70883 1.2668426   .009171908   1.476314   .016509434  -4.4464383  .4596698   3.260224 0 0    .05508011   .02548483  .11428571   .680368 0 1
   4746   .1315469    .1866154    .5978368     .0905759  -.00666093    .13274054 1  10.35383  .7153329     .2176977   .3971931      .090625    .6613357  .2988515  -7.273396 0 0   .004716831    .1512573   .3048191  .9179463 0 1
   8291   .9512845   -.8380952     .374359    -.1827509  -.18020944    -.1121779 0 10.657142  .1970585     .7829823   .2645092    -.7334026   2.1661377  .3489039  -.4162302 1 1 .00014119309    .1951053          0   1.51777 0 1
  23630   1.639713    .9033894  -.24660163     .0155843   .13976352    .08782122 1  12.42276 .57877296     .1575146   .3357702   .020157993    1.817896  .5191301   .7059633 0 1    .04430515   .09513227   .2187913   .591377 0 1
  85500  1.6568485  -.03828402    .3954857    .05874339   .05250736    .08314705 0 14.693217 .28731462     .0650289   .9024743    .10746881    10.62788  .4612735   .7264649 0 0   .011973175  .035545364          0  .8649753 0 1
      0   .7868181    1.160005     .785594     .0566723   .04556328     .0839752 1 11.287843  .4304715    .01498579   .6890693    .07794333   31.579166   1.14194   1.293401 0 0   .007113783           0          1  .3980957 0 1
   6901   .4593699    .1126544    .8380994     .1020315    .0488463    .08312255 1 12.933455  .3696268   .030249983   .4934379    .18483475    20.55546  .3387639   1.909736 0 0    .05714479   .01667186 .001591435  .9903705 0 1
    512   .5898263   1.0816588   .23142298    .08495575   .12024336    .09621128 0 10.495708  .7191095   .009849942   .9990001    .05909965    9.899611  .4882628   .4696638 0 0    .07331305  .014159292          0  1.424958 0 1
    191   .3604599    .3409091    .6296296    .10511363   -.5113636     .1143466 0  7.249926 1.0007102    .06799573   .9936125    .05268779 -.002816901  .3468621  -2.260428 0 0    .05965909    .1356534          0  .8188463 0 1
    830  .19537506  -.07185169    .1620964    .03139319   .08896304    .09234674 1   10.6586  .4995418     .0417751    .735171    .03621774    8.833679 .29599202    .459711 0 0    .01642503  .019503254   .4613887  .9588554 0 1
   4559   .8783939   -.2182814    .8732979    .05081438  .016800003     .0670531 0  13.87552 .19899704   .016927127  .27461383    .20033713    99.60663  .3860491   .7304402 0 0  .0042925286   .00429347          0 1.3013126 0 1
   1462  .15488896    .3197338    .7479535    .08280807   .06342578    .09183513 1 12.087785  .2735525     .0660887   .3787315     .2195595   15.812937  .4407531   .7047999 0 0   .027137455  .008227905   .6699029 1.0542964 0 1
   7114   .9355339    .1179966    .4165798    .05792898  .035487738    .06234727 1 14.215917 .25376582   .012920628   .5202097     .1501617    79.22765  .3421205   .5258909 0 0    .02233805   .00476672  .04368867  .7721423 0 1
    475  1.9395814   -.3373494   1.7195282    -.4039112   -.6363295   -.21399023 0  7.885705 .12297856     .6840391   .1559633   -1.1844941     .881997   .684006  -.3007007 0 0 .00003951632    .1786386          0 2.1267529 0 1
  14100   .7135102   .05936719    .4301762    .07505184   .04411036    .07141167 0 13.747254 .29292703   .022260815  1.3150585    .11067256    28.22312  .9551014   1.458148 0 0   .035759367   .01509602          0  .6797072 0 1
      0  1.1055976  -.05087379  -.02940068    .12046976     .094288   .026139664 1  10.76878  .9871827   .018603861  1.1326724    .05722112    .1863525   .879885   1.319996 1 0    .02693943           0          1 .30312315 0 1
   1800   1.079673   1.7816303   -.6865287    .06449573   .05947661   .011293027 0 12.895403 .51420915   .003741426  1.3479747    .05341925    55.30743 .25078338  1.1568834 0 0     .1591062 .0045172106          0  .9113573 0 1
     19  .27584097  -.13928914  -.25443152   .025680253   .09195717   .033220414 0  9.814766  .7900776  .0007497435   .7525588   .018546287   103.83784 1.1296326  -8.892572 0 0   .010436018 .0010381379          0  .6017162 0 1
    507    .915879    1.674931    .4683037    .15519144  -.54450923     .4451995 1  8.755737    2.5902    .04822013  .15170316    .05202281   -7.722265  .9050007   5.221335 0 0   .069796756   .07988026   .4446878  .4466296 0 1
  16679   1.422881    .2464466   .14613536    .06737555    .0674186   .009639743 0  13.31126 .35184565    .05279468   .4866918    .12880394    12.24148 .32403725   .6462839 1 0   .010105007   .02761616          0  .5585275 0 1
  77000   .6888515  -.13131616    .1669228    .04602952   .06681704    .03537373 0 16.253428  .3221193   .007651794   1.728579    .05237007    53.89705  .4877479  .18457054 0 0   .033539534  .006725376          0 1.1512874 0 1
  18000   .5578642   .15622756    .4494443    .04723259   .04621108    .06043923 0   17.5319 .13590921  .0008174016   2.940766    .08818854   1015.0766  .7987891   .3924578 0 0   .011771665 .0004377892          0  1.324038 0 1
    369 -.26190367   -.6797853   -.2289655   .032943502  .028249053    -.3894334 1 10.097573  .5977187    .06378651   .4224595    .03874655   3.3732734  .9538281  1.0467317 1 1   .007782902   .01519519   .7198178  .3996292 0 1
   1286   .2705766   .17528483   -.2367893     .1248704   .15508814     .1645682 1  8.817446  .9589691    .09798842  1.0271857    .06423347   .08634663  .6593108   2.761496 1 0    .05006666    .1904903          0  .3095998 0 1
 199000   .3851978   .22857653   .06568426    .05040561    .0530143    .09341995 0 17.356474 .18359353   .013177062  1.3842753     .1151503    81.64095   .488597    .665803 1 0    .00579708  .005768095          0   .978204 0 1
   3500   .8035917   -.6847477  -.19472894    .05644667   .07534298    .03004029 0 12.930668  .8600244   .007077856  .39295775     .0471183    7.407564  .6778795   .9599862 0 0    .04142652  .008479114          0  .9087718 0 1
    563   .5435368   2.3739445   1.0138991  -.002723505  -.25293073     .3179396 1  9.041329  1.435524    .12923124  1.1127609 -.0008979815   -.4987795  .4141821  2.3829284 1 1    .00580225   .06666667   .8299094   .199535 0 1
   1479  .55211645   .13916488   .03961256    .07382355   .09229762    .09422503 1 10.221869  .4410503     .2043382  .26583114    .13223033    2.463931  .5751358   .7816202 1 0   .006364099   .05378573   .5285304  .3692825 0 1
    847  .09467015   .18790182     -.22614   -.08684996   .13459079   .016730605 0  9.146761 1.3249147    .02538588   1.683584  -.024426794  -1.8820988 .12468278   .9318044 0 1     .0801364   .09026001          0   .969691 0 1
   1220  1.0477142   .04606286    .3382382    .07668137   .08764774    .05940986 0 10.780122  .7621941    .01901793   .7513924    .05744349   4.3140807  .5105945   .8283381 1 0    .07963626   .02538705          0  .6235829 0 1
     84   .3753218   .23267895   -.3318157    .09607036   .09663416    .04296104 1  9.783408  .7843491   .005321773  1.0395342    .06005498    7.935685  .4299635   .4763911 1 0   .002875345  .004735863   .4437086  .4799102 0 1
   3000   .8902683    .3481969  -.13456452    .02336627   .09930666  -.018586807 0 14.448406  .6845256 .00052863435   3.402638   .007753304   66.006226  .6574111   .6916955 0 0    .02602153  .001593155          0  .8934448 0 1
    526  .27223036         -.2   -.3344156   -.48590755  -.24859075    -.7752354 1  7.480992 1.4932356    .20184727   .6757267    -.1941879  -.47997805  .5123495   -2.22662 1 0    .05524239   .29650506   .4129464  .6074911 0 1
    153  .51591164  -.51007974   .08582677    .06974866   .06054642 -.0016823122 0 10.992756  .2948252   .006389643   .3663338     .1731468   120.10602  .9299818 -17.297926 0 0   .007990982 .0025739376          0  .7075083 0 1
  25800  1.1560158 -.007532011    .3473939   .036453754   .04733108    .03233801 1  13.43031  .1868255    .12245667  1.0881196    .09344386      10.438  .3663986  1.8752563 1 0   .008231493   .03792366  .20615384  .6308936 0 1
   8928    .472752     .786253   .25188857     .0602607     .111513    .15232375 1  9.592401 1.0456562     .3300316   .8185616   .031689636 -.037230786  .3041864   .4769854 1 0    .04183444    .5562721 .029143106  .5909731 0 1
  36952   .6643065   -.0228583   .06556972    .02844771   .04716086   .015506564 1 14.109152  .2389445    .05362348   1.470825     .0481846   11.141252 .54942816   .6691908 1 0      .010331   .02754933  .12980407  .6815835 0 1
    368  1.1339529    .5497107    .8248538   -.04556734  -.05955335     .0918114 1 8.3968315  2.212046   .033076428  .27024272  -.016217085   -5.930464 .12468278  1.2529162 0 1    .04646966   .08301376  .10679612  .4770026 0 1
    977     .96303    .7602229    .3111564    .10460012   .14587015    .12534915 1   9.77241  .8654734    .04397866   .7282487     .0699314   1.2453825  .9429465   .9103946 1 0   .007695377   .05569173  .15337954  .2481939 0 1
      0  1.3101172        .452    .7985612    .13179572    .0689574    .12967756 1  8.354439 1.2056955   .005825242  .30685145     .0836445   -22.41026 1.8053495  -5.618548 0 0   .021887504           0          1 .23316105 0 1
  11252   .8462864     .658681       .6328  -.033746257   .04948204    .09290807 1 11.528326  .7670947     .0697029  1.0722464   -.02122928   1.1478767  .5307518  -7.629505 1 1   .021260044   .11080038          0  .2748236 0 1
    171  1.3836466  -.23528187    .6999727     .2138885   .13538073     .3066891 0  9.383033  .9007152  .0082985535   .9248949    .17771523    3.920266  .6695033  2.7226675 0 0    .05679428  .014387884          0  .6900021 0 1
    131     .60088   -.1754386  -.22799097    -.4058957  -.25018898    -.2887377 0  7.187657  .8155707    .09343795  .29935125   -.38302425    .7134503  .5742796  -.7907938 0 0   .006802721   .09901738          0  .8824686 0 1
   1339    .667627  -.09494165   -.0582419   .029312566   .05132765     .1123444 0  9.699349  .8531919     .0722612   .3318479    .02579601        .855  .3154444  1.5222405 1 0   .007052186   .08211198          0  .3628131 0 1
    794  1.2628312  -.25298217  -.11590268   -.09957224   .05394487    .07485741 0  8.344743  .8861692    .18612283  .14400643   -.09821847   .33519945   .224369  1.8733927 1 1     .0798479    .1886882          0 .29699507 0 1
   2000   .6387894  -.14519644    .3481969  -.017705912   .02225886   -.03035299 0  14.49696  .5225773  .0003577817   4.411423   -.00626118    188.7482  .6574111   .6916955 0 0    .04148242 .0010117664          0 1.0526133 0 1
  48597   .7397297   .06556972  .007098887    .05496011   .05724255   .033152267 1  13.95611 .27240342    .06210741  1.5246136    .07991717   9.2439375 .54942816   .6691908 1 0   .017785123   .04222294   .0114524  .6054171 0 1
1248000  1.6608844    .0814416   .12119638    .04898749   .04438806    .06512196 0 16.432714    .29502    .07311072   3.224202    .03930873    3.580414  .1742754   1.603011 0 0     .0305898   .09111234          0 1.0148379 0 1
    305   1.368572   .12765957  -.25289017   -.05035669   .18067795   -.06266611 0   9.97334   .486082    .02293923   .2753957   -.08122744   19.168695 1.1583688 -1.5331154 0 0   .010117965  .014221103          0  .7111887 0 1
   2800   .6012924    .4429955  -.05043437   -.03853382    .1295728    .12281247 0 13.003053  .6181186   .002476123  3.1224935  -.015122037   31.382593  .3304648   .5849913 0 0    .12010834  .006309632          0  1.331281 0 1
   1520  .07115827    .5671447    .4201313    .04160593   .03769106    .04608304 0 10.779414  .3516097    .05699288   .5795084    .07491563    17.03337 1.0404801  -3.748522 0 0   .011723793   .03165216          0   .659989 0 1
  29480  1.2815735    .3971923 -.035742987   .035525627  .030658275    .04045431 1 13.933335  .1968469    .10366073   .3822416    .13056573    13.91565  .7083763   .8698344 0 0  .0023119035   .02620335 .070969366  .6641484 0 1
  10300  .15835616    .3989594   -.1543824     .0848807     .088687    .04009313 1 13.577463 .04593375    .03721398  13.315568    .16821724    28.91287  .3142696   .7038307 1 0    .03895123   .01306833  .30405405   .737729 0 1
      0   .5454001   -.7234849    .6296296   -.05953278 -.004144687   -.17906933 1  9.963264 .53913903    .06668513  1.2073905   -.05002375    5.280626 1.0931014  -.6432657 0 0   .029625094           0          1 .50671303 0 1
    402   1.072761   1.3871777  -.14437415   -.20700546   .04909561    .08699397 1  8.155649 2.6029284    .04106604   .3161262   -.06042575   -5.864496 .12209907  1.2529162 0 0    .09388458   .11541774  .17959183  .8271886 0 1
    635   .4253995   2.2909698  -.09156626    -.6973303  -.18138826   -.25141114 1  8.787983 .29229596    .11290322  2.0093946    -.7927506    3.901598  .4138888  -.3705606 0 0  .0021357741   .09687261 .024577573  1.606765 0 1
    115   .6360535   1.4315364    1.320891    .16727147   .07015725    .22757906 0  8.663369  .6806636   .011451902   1.549378    .09639514    9.148515  .7175088   .7536366 0 0    .08363573  .019872127          0  .5940968 0 1
     15   .8485748   -.7033333   -.3863636   -.02251771  .011792682    -.3696011 0  9.933337  1.209599  .0003946953   .5247342   -.01220924   -59.16438  .8823578 -1.4293134 0 0    .18480055 .0007279433          0  .6893558 0 1
    661   .4790399   .04531737  .005360032     .0805192   .06532292    .07703672 0  9.156518  .4662305    .08652965   .7290629    .09988219   4.1493025  .3200469  2.2275991 0 0   .023533136  .069755174          0  .5806087 0 1
   5328  1.0020541  -.07346867    .4440678    .04042749  .036392663     .0450417 1  14.60817  .1219062    .01610718   .4935338     .2220424   157.68033  .4652563   .6577917 0 0   .005686962  .002411663  .17765087  .8055208 0 1
   1800   .8912895   .20724466   .04678117    .21492687    .1550666     .1539264 0  12.76802 1.0042273   .001362604   2.749645    .05707797   -.4237143  .3304648   .5849913 0 0    .14052911   .00513088          0  1.180903 0 1
   2236   .8962447  .032048907   -.4016627    .10914207   .09035595   .026201705 1 10.177172 1.5661697    .04275149   .7794289    .03916271  -2.6956365 .37728125  -9.280164 1 0    .09993915   .08503194  .28630707  .5580445 0 1
   9600   .7670774   -.4044494   -.1180901   .029557297  -.01642072  -.073345885 1 11.422432  .6841967    .10024302     1.6336   .016403401    .8484706  .3663986  1.8752563 1 1    .04159916   .10509261   .4181818  .3353202 0 1
end
label values cap CAP
label def CAP 0 "Capitalizers", modify
label def CAP 1 "Expensers", modify

------------------ copy up to and including the previous line ------------------

[Rich Goldstein]

you say you want "a t-test on multiple variables" but that does not appear to be what you are showing which looks like several t-tests each one on one variable; for that, assuming you are using version 17, you want the -table-command; the following blog entry deals quite directly with this (though you may want to look at the 3rd blog in the series also): https://blog.stata.com/2021/08/24/cu...istical-tests/

[Anthony Killeen]

This will get you multiple t-test results, with a similar layout to the table you show. The results will be in a frame named sumstats.

frame create sumstats str8(variable) mean1 sd1 min1 median1 max1 mean0 sd0 min0 median0 max0 diff P

foreach var of varlist rdexp-fearns lnsize-cvearn scapex-imr{ //this ignores pastbeat, zerobeat, GAAP and IFRS
    qui ttest `var', by(cap)
    local p = `r(p)'
    local diff = `r(mu_2)' - `r(mu_1)' //difference in means
    
    forvalues i = 0/1 {
        qui summ `var' if cap==`i', detail
        local mean`i' = `r(mean)'
        local sd`i' = `r(sd)'
        local min`i' = `r(min)'
        local median`i' = `r(p50)'
        local max`i' = `r(max)'
    }        

frame post sumstats ("`var'") (`mean1') (`sd1') (`min1') (`median1') (`max1') (`mean0') (`sd0') (`min0') (`median0') (`max0') (`diff') (`p')
}

frame change sumstats

[Cristiana LI]

This will get you multiple t-test results, with a similar layout to the table you show. The results will be in a frame named sumstats.

frame create sumstats str8(variable) mean1 sd1 min1 median1 max1 mean0 sd0 min0 median0 max0 diff P

foreach var of varlist rdexp-fearns lnsize-cvearn scapex-imr{ //this ignores pastbeat, zerobeat, GAAP and IFRS
qui ttest `var', by(cap)
local p = `r(p)'
local diff = `r(mu_2)' - `r(mu_1)' //difference in means

forvalues i = 0/1 {
qui summ `var' if cap==`i', detail
local mean`i' = `r(mean)'
local sd`i' = `r(sd)'
local min`i' = `r(min)'
local median`i' = `r(p50)'
local max`i' = `r(max)'
}

frame post sumstats ("`var'") (`mean1') (`sd1') (`min1') (`median1') (`max1') (`mean0') (`sd0') (`min0') (`median0') (`max0') (`diff') (`p')
}

frame change sumstats

Fabulous! Hit the bullseye!
Many thanks！