Hello everyone,
I have a full matrix of results after running a mlogit estimation by country. I would like to represent the results in a map instead of a "classic" table, since I have one estimation result per country. The matrix looks like this
DOM_GTIa_b corresponds to the beta coefficient of my variable of interest (GTIa) on internal migrations (DOM) (outcome 2 of my mlogit).
DOM_GTIa_p corresponds to the corresponding p-value.
INT suffix stands for international migrations (outcome 3 of my mlogit).
I'd like to create two maps, one for internal migrations, the other for international ones. I would like to include all beta coefficients I have here in my matrix of results, but with a particular emphasis on the ones being significant at 5% (p<=0.05). Ideally, I thought about highlighting these particular countries with slashes (I'm opened to suggestions).
My current spmap code is such as:
But with this code I obtain a map without any distinction on the p-values obviously. Any idea how to do that please? Any help would be much appreciated.
Thank you in advance,
Killian
I have a full matrix of results after running a mlogit estimation by country. I would like to represent the results in a map instead of a "classic" table, since I have one estimation result per country. The matrix looks like this
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str52 origin float(o converged nobs nalt nresp ndfm npar nwaves nsubwaves DOM_GTIa_b DOM_GTIa_se DOM_GTIa_z DOM_GTIa_p INT_GTIa_b INT_GTIa_se INT_GTIa_z INT_GTIa_p) "Albania" 1 1 970 0 3 24 34 2 2 -.12976843 .06936996 -1.870672 .06139055 .01470666 .0755269 .19472083 .8456115 "Algeria" 2 1 3084 33 3 27 38 4 5 -.027323693 .02498631 -1.0935466 .27415386 -.0912853 .07684368 -1.1879352 .23485893 "Angola" 3 1 1477 0 3 24 34 2 2 .3213637 .16525 1.944712 .05180966 1.3229 .18704215 7.072738 1.5190604e-12 "Argentina" 4 1 2785 0 3 30 40 5 5 -.007761759 .03415157 -.22727385 .8202108 .04489442 .13897046 .32305005 .7466573 "Armenia" 5 1 3693 0 3 34 44 7 7 -.1061456 .07207699 -1.4726696 .14084014 .01333367 .11064167 .1205122 .9040774 "Australia" 6 1 1152 0 3 26 36 3 3 .07956897 .06095408 1.305392 .19175935 .08964764 .24161074 .3710416 .7106065 "Austria" 7 1 1776 0 3 26 36 4 4 -.024301853 .06482402 -.3748896 .7077426 -.21141933 .26632944 -.7938263 .42729655 "Azerbaijan" 8 1 2541 0 3 33 44 7 7 .12076923 .08159624 1.4800832 .13885105 .04918098 .14792563 .332471 .7395336 "Bahrain" 9 1 3066 0 3 28 38 4 4 -.13126999 .026468387 -4.959501 7.06745e-07 .001847397 .10302607 .017931355 .9856936 "Bangladesh" 10 1 5219 0 3 34 44 7 7 -.02151143 .05887154 -.3653961 .7148157 -.4054044 .19024552 -2.1309536 .03309296 "Belarus" 11 1 4029 0 3 34 44 7 7 .14699467 .032421812 4.53382 5.792633e-06 .13709433 .0934105 1.4676545 .1421981 "Belgium" 12 1 1596 0 3 26 36 3 3 .2250023 .0799418 2.814576 .004884162 .10730167 .2732547 .39268005 .6945558 "Benin" 13 1 3834 0 3 28 40 5 5 0 0 . . 0 0 . . "Bhutan" 14 1 2235 0 3 26 36 3 3 .05105785 .07547566 .676481 .4987353 .7638986 .3661446 2.0863302 .036948714 "Bolivia" 15 1 4125 0 3 32 42 6 6 -.07310887 .03851023 -1.8984274 .0576398 .002404557 .10276804 .023397906 .9813329 "Botswana" 16 1 2119 0 3 24 36 3 3 0 0 . . 0 0 . . "Bulgaria" 18 1 2657 0 3 32 42 7 7 -.0022955062 .0710047 -.03232893 .9742097 -.013702468 .10736345 -.12762693 .8984442 "Burkina Faso" 19 1 4426 0 3 32 42 6 6 .02428656 .07466631 .325268 .7449782 .302009 .12197249 2.476042 .013284806 "Burundi" 20 1 2185 0 3 26 36 3 3 -.026132485 .04184137 -.6245609 .5322593 .3114715 .1341154 2.322414 .02021066 "Cambodia" 21 1 4267 0 3 32 42 6 6 .24135967 .09024387 2.674527 .007483474 .25230622 .4154064 .607372 .5436041 "Cameroon" 22 1 3942 0 3 32 42 6 6 -.02224585 .01969297 -1.1296341 .25863042 .10795724 .04598539 2.3476424 .01889265 "Central African Republic" 24 1 1622 0 3 24 34 2 2 .16186996 .07203152 2.2472103 .024626594 .19282487 .1792534 1.0757111 .28205648 "Chad" 25 1 5831 0 3 34 44 7 7 -.022808196 .02091916 -1.0903016 .27558026 .0817886 .035410184 2.3097477 .020902127 "Chile" 26 1 3272 0 3 32 42 6 6 .070772186 .02123457 3.3328755 .0008595338 .13987544 .071867846 1.9462868 .0516203 "Colombia" 28 1 3556 0 3 34 44 7 7 .010944182 .02206466 .496005 .6198909 .09966103 .064829744 1.5372733 .1242264 "Costa Rica" 29 1 3738 0 3 30 42 6 6 0 0 . . 0 0 . . "Croatia" 30 1 1131 0 3 24 34 2 2 -.8031086 .3708303 -2.165704 .030333815 -.336095 .4571997 -.7351164 .4622686 "Cyprus" 31 1 1991 0 3 28 38 4 4 -.1672957 .07304565 -2.2902896 .022004535 .20944045 .2079715 1.0070633 .31390435 "Czech Republic" 32 1 3138 0 3 32 42 7 7 .05053426 .05129416 .9851855 .324533 -.5692547 .28674084 -1.9852586 .04711571 "Côte d'Ivoire" 33 1 2792 0 3 28 38 4 4 -.012926582 .022134684 -.58399665 .5592225 -.08983453 .04873696 -1.8432528 .06529211 "Democratic Republic of the Congo" 34 1 4132 0 3 31 42 6 6 .07035348 .018477144 3.807595 .00014032493 .11695943 .033849396 3.4552884 .0005497044 "Denmark" 35 1 1416 0 3 26 36 3 3 .05319685 .05018159 1.060087 .28910503 -.04196068 .1731983 -.24226958 .8085713 "Dominican Republic" 36 1 3686 0 3 34 44 7 7 -.0590481 .05486678 -1.0762085 .28183404 .05575668 .09423537 .59167475 .55406845 "Ecuador" 37 1 2619 0 3 30 40 5 5 -.05710624 .04404862 -1.2964363 .1948252 .024705335 .11607515 .21283914 .8314524 "Egypt" 38 1 3778 0 3 30 40 5 5 .06224888 .02732705 2.2779217 .022731246 -.16653553 .072495446 -2.2971861 .02160816 "El Salvador" 39 1 4244 0 3 30 42 6 6 0 0 . . 0 0 . . "Estonia" 40 1 800 0 3 22 34 2 2 0 0 . . 0 0 . . "Ethiopia" 41 1 2313 0 3 24 36 3 3 -.09492033 .035950456 -2.640309 .008283036 .009260411 .08299669 .11157567 .9111599 "Finland" 42 1 924 0 3 26 36 3 3 .06856895 .07416604 .9245331 .3552088 -.09643614 .22761875 -.423674 .6718036 "Gabon" 44 1 3623 0 3 28 40 5 5 0 0 . . 0 0 . . "Georgia" 45 1 3564 0 3 34 44 7 7 .001418286 .04032076 .035175085 .9719401 .09584304 .1409213 .6801175 .4964301 "Germany" 46 1 1512 2 3 28 38 4 5 -.13734046 .064169586 -2.1402733 .032332674 -.1224961 .22540124 -.5434579 .5868146 "Ghana" 47 1 3441 0 3 30 40 5 5 -.012165073 .04050349 -.3003463 .763913 -.036758944 .07704773 -.4770931 .6332958 "Greece" 48 1 3315 0 3 31 44 7 7 .005809367 .02549153 .22789402 .8197286 .04606277 .05196906 .8863498 .3754291 "Guatemala" 49 1 2888 0 3 28 38 4 4 .05378345 .03990714 1.3477148 .17775014 .09446277 .07977389 1.1841315 .23636103 "Guinea" 50 1 3176 0 3 30 40 5 5 .10948043 .04519242 2.42254 .01541244 .11043192 .05833423 1.8930895 .05834597 "Haiti" 51 1 1773 0 3 32 42 6 6 -.1062982 .17865923 -.5949774 .5518586 -.25396657 .3568481 -.7116939 .47665435 "Honduras" 52 1 4276 0 3 34 44 7 7 .006012908 .029601675 .2031273 .8390355 .04798345 .05443902 .8814165 .3780924 "Hungary" 53 1 780 0 3 24 34 2 2 .1520987 .12554277 1.2115288 .2256928 .1764534 .17035283 1.0358113 .3002902 "India" 54 1 21817 0 3 34 44 7 8 .13563919 .014895702 9.105928 8.553145e-20 .08940367 .1235207 .7237949 .4691916 "Indonesia" 55 1 5074 0 3 30 44 7 7 .11743207 0 . . .57115334 0 . . "Iran" 56 1 3032 0 3 30 40 5 5 .0830548 .01996583 4.1598477 .000031845986 .27585882 .05727866 4.816084 1.464031e-06 "Iraq" 57 1 2842 0 3 26 36 3 4 .03987381 .02660379 1.498802 .13392502 .1069322 .0512499 2.086486 .03693461 "Israel" 58 1 3760 0 3 32 42 6 6 .00398869 .04455171 .08952945 .9286612 .3831985 .19396946 1.975561 .04820451 "Italy" 59 1 1350 12 3 28 38 4 4 -.08993775 .05535474 -1.6247525 .1042153 -.19138093 .12206419 -1.5678713 .11691117 "Jamaica" 60 1 291 0 3 22 32 1 1 .57796067 1.1951133 .4836032 .6286675 .06305569 2.477118 .025455264 .9796918 "Jordan" 61 1 6108 0 3 33 44 7 8 -.015606663 .025536615 -.6111485 .5411013 .05488089 .08172279 .6715494 .5018706 "Kazakhstan" 62 1 4275 0 3 34 44 7 7 -.010219 .035766106 -.28571743 .7750946 .08280636 .1542963 .5366711 .59149486 "Kenya" 63 1 4429 0 3 32 42 6 6 -.00466262 .015892455 -.2933858 .7692273 .021940624 .05953586 .3685279 .7124797 "Kosovo" 64 1 1329 0 3 24 34 2 2 .12502153 .05741621 2.1774607 .02944622 -.1812762 .1092144 -1.6598196 .09695075 "Kuwait" 65 1 4509 0 3 31 42 6 7 .033569094 .02467113 1.360663 .1736202 .05583004 .05034 1.1090592 .26740468 "Kyrgyzstan" 66 1 4492 0 3 34 44 7 7 .04069415 .05300311 .7677692 .4426244 .0228309 .09983688 .22868203 .8191161 "Latvia" 68 1 2666 0 3 30 42 6 6 0 0 . . 0 0 . . "Lebanon" 69 1 5671 0 3 34 44 7 8 .0091223195 .032434504 .28125355 .7785159 .05743228 .08312149 .6909438 .4896009 "Lesotho" 70 1 687 0 3 22 32 1 1 .06033796 .31020415 .1945105 .8457762 .06780086 .6841646 .09910022 .9210587 "Libya" 71 1 1490 0 3 24 34 2 2 -.06241156 .03126206 -1.9963994 .04589046 -.12591198 .04282713 -2.9400055 .003282064 "Lithuania" 72 1 3004 0 3 32 44 7 7 0 0 . . 0 0 . . "Luxembourg" 73 1 515 21 3 17 32 1 1 0 0 . . 0 0 . . "Macedonia" 74 1 922 0 3 24 34 2 2 .06169864 .06203803 .9945294 .3199652 -.029748766 .08048767 -.3696065 .7116757 "Madagascar" 75 1 3822 0 3 30 40 5 5 -.025226656 .027063074 -.9321431 .3512626 -.04903199 .11437062 -.4287114 .6681333 "Malawi" 76 1 1547 0 3 22 34 2 2 0 0 . . 0 0 . . "Malaysia" 77 1 3545 0 3 26 40 5 5 .03895926 0 . . .26040888 0 . . "Mauritania" 79 1 6078 0 3 34 44 7 8 -.02401965 .02962074 -.8109065 .4174194 .2115876 .0699957 3.022865 .002503937 "Mexico" 80 1 2645 0 3 28 38 4 5 -.07626173 .03754194 -2.031374 .04221708 .09839313 .09078282 1.0838299 .2784402 "Moldova" 81 1 3439 0 3 32 42 6 6 .03090454 .063426904 .4872466 .6260836 .08377279 .10472643 .7999201 .42375705 "Mongolia" 82 1 3451 0 3 28 40 5 5 0 0 . . 0 0 . . "Montenegro" 83 1 1016 0 3 24 34 2 2 -.011387386 .11177985 -.10187335 .9188572 .05431838 .20086843 .27041772 .7868389 "Morocco" 84 1 2735 0 3 26 36 4 4 .012853036 .03076947 .4177204 .6761515 .05956033 .09554326 .623386 .5330309 "Mozambique" 85 1 560 0 3 20 32 1 1 -.025699314 .04721348 -.54432154 .5862202 .07667636 .2171748 .3530629 .7240413 "Myanmar" 86 1 2536 1 3 28 38 4 4 -.05435925 .04203175 -1.2932903 .1959107 -8.914063 .4636493 -19.225874 0 "Namibia" 87 1 562 0 3 20 32 1 1 0 0 . . 0 0 . . "Nepal" 88 1 5116 0 3 34 44 7 7 .008803531 .06132296 .1435601 .8858479 .10543472 .3498898 .3013369 .7631576 "Netherlands" 89 1 1205 0 3 26 36 3 3 .010910528 .05858107 .18624663 .8522514 .08331673 .2316848 .3596124 .719137 "New Zealand" 90 1 1086 0 3 26 36 3 3 -.06923419 .1155389 -.5992284 .5490205 .06389091 .2422298 .26376155 .7919636 "Nicaragua" 91 1 3628 0 3 32 42 6 6 -.01997141 .04976946 -.4012784 .6882152 -.14595287 .11547628 -1.2639207 .2062585 "Niger" 92 1 5691 0 3 34 44 7 7 -.02223478 .021884413 -1.0160099 .3096247 -.06146595 .0394048 -1.5598593 .11879313 "Nigeria" 93 1 5692 0 3 34 44 7 8 -.05395183 .015662184 -3.4447196 .0005716524 -.14294887 .03714282 -3.848627 .00011878164 "Norway" 94 1 507 1 3 15 32 1 1 .07600389 0 . . -6.473337 0 . . "Pakistan" 95 1 5343 0 3 34 44 7 7 -.04995336 .08557837 -.5837147 .55941224 -.55540514 .4205642 -1.320619 .1866284 "Panama" 96 1 4057 0 3 34 44 7 7 -.11600205 .2729485 -.4249961 .6708395 -7.677625 .3728125 -20.593796 0 "Paraguay" 97 1 4120 0 3 34 44 7 7 -.06078538 .07659777 -.7935659 .4274482 .21925806 .12651429 1.7330694 .08308333 "Peru" 98 1 3030 0 3 34 44 7 7 .021997254 .03593865 .612078 .5404862 -.07611353 .08475634 -.8980276 .3691708 "Poland" 99 1 3248 0 3 30 42 7 7 0 0 . . 0 0 . . "Portugal" 100 1 1535 0 3 26 36 4 4 .034176577 .17446056 .19589858 .8446895 .38357905 .36726505 1.0444202 .296291 "Republic of Congo" 101 1 3439 0 3 30 40 5 5 .0021089418 .09938148 .02122067 .9830696 -3.8667054 .0856987 -45.11977 0 "Romania" 102 1 2009 0 3 34 44 7 7 .3689977 .4405231 .8376355 .4022355 -1.3828766 1.0751041 -1.2862724 .198348 "Russia" 103 1 9413 0 3 30 44 7 9 -.07009073 .02418 -2.898707 .003747053 -.02718243 .0870212 -.31236565 .7547626 "Saudi Arabia" 105 1 4272 0 3 30 40 5 5 .11043423 .021319315 5.180008 2.218757e-07 .012755977 .04997024 .2552715 .7985134 "Senegal" 106 1 5134 0 3 34 44 7 7 .011229874 .02965718 .3786561 .7049432 .08325405 .04317566 1.9282634 .05382236 "Serbia" 107 1 1382 0 3 32 42 6 6 -.3021757 .13928722 -2.169443 .03004908 -.2111873 .1751461 -1.205778 .22790307 end
DOM_GTIa_p corresponds to the corresponding p-value.
INT suffix stands for international migrations (outcome 3 of my mlogit).
I'd like to create two maps, one for internal migrations, the other for international ones. I would like to include all beta coefficients I have here in my matrix of results, but with a particular emphasis on the ones being significant at 5% (p<=0.05). Ideally, I thought about highlighting these particular countries with slashes (I'm opened to suggestions).
My current spmap code is such as:
Code:
rename DOM_GTIa_b GTI_Internal_b format (GTI_Internal_b) %12.2f spmap GTI_Internal_b using "worldcoor.dta" if NAME_0!="Antarctica", id(id) fcolor(RdBu) clmethod(custom) clbreaks(-0.80 -0.1 0 0.1 0.58) ndocolor(gs13) ocolor(none ..) osize(vvthin) legstyle(2) legcount legend(size(*1.5))
Thank you in advance,
Killian
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