I am using Stata 14 SE, and have a question about using margins for a time-variant variable in a mixed-effects model.
My dependent variable Y, and three independent variables (X) are measured at two time-points. While X1and X3 are measured in each district at time 1 and time 2(wave), X2 is measured at the province-level at time 1 and 2. Districts are nested in provinces. Basically I have multi-level repeated measures data. My control variables (Z) are time-invariant. Data example is below.
The code I use to model the effect of X1 X2 and X3 on Y is:
Code:
mixed Y i.wave i.X1 c.X3 c.X2 Z1 Z2 ||province: ||district_no:
Code:
mixed Y i.wave i.X1##c.X3 c.X2 Z1 Z2 ||province: ||district_no:
Code:
margins X1, at (X3(-.15(.03).15) marginsplot
When I use this variable in the model instead of X3, both the estimates and the marginsplot change completely. I am not sure why the coefficient of X3 almost doubles when I use the difference variable instead.
Should not their substantive effect be exactly the same? The direction of effect is the same but the coefficient almost doubles.
But more importantly, how does one go about plotting the marginal effects of two time-variant variables in a mixed model?
I appreciate your help.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double Y byte wave float X1 double X3 float(X2 Z1 Z2 province) int district_no float DifferenceinX3 .5008916001877053 1 0 .8836196467457053 0 0 0 1 1 0 .5701738334858188 2 0 .891889725917615 .5954652 0 0 1 1 .00827006 .25843545684528696 1 0 .8517262864682598 0 0 0 1 2 0 .33096601673721704 2 0 .8558748788826122 .5954652 0 0 1 2 .0041485853 .2314806361495061 1 0 .8671302188663923 0 0 0 1 3 0 .28064805600966664 2 0 .8749831214675643 .5954652 0 0 1 3 .007852902 .4701195219123506 1 0 .8039459375485475 0 0 0 1 4 0 .5468765275197967 2 0 .825685903500473 .5954652 0 0 1 4 .021739945 .45914704629798625 1 0 .8386024120303737 0 0 0 1 5 0 .5308816595945309 2 0 .8622581288649511 .5954652 0 0 1 5 .023655705 .5529871977240398 1 0 .9015807301467821 0 0 0 1 6 0 .5972691441441441 2 0 .9105439383410197 .5954652 0 0 1 6 .008963187 .23223635003739715 1 0 .869795996674554 0 0 0 1 7 0 .2716732739920712 2 0 .8649493081680801 .5954652 0 0 1 7 -.00484667 .42910860429108605 1 0 .8222902932232359 0 0 0 1 8 0 .5013144023806029 2 0 .8456993069130976 .5954652 0 0 1 8 .023409005 .4536984981126014 1 0 .8757469606429013 0 0 0 1 9 0 .5270582609388699 2 0 .8802646998000965 .5954652 0 0 1 9 .0045177345 .4836112708453134 1 0 .7833479404031551 0 0 0 1 10 0 .5462431001464458 2 0 .8043728423475259 .5954652 0 0 1 10 .021024877 .36644963615473 1 0 .8615101724805369 0 0 0 1 11 0 .4484892121448794 2 0 .8800895139308706 .5954652 0 0 1 11 .018579356 .2582014753593243 1 0 .8491196205853588 0 0 0 1 12 0 .3228475641790513 2 1 .8528333602230218 .5954652 0 0 1 12 .0037137566 .35363741339491916 1 0 .8177992041628406 0 0 0 1 13 0 .4731265652090156 2 0 .8134437035333794 .5954652 0 0 1 13 -.004355507 .32956786802940646 1 0 .8485232696897375 0 0 0 1 14 0 .37584912406149446 2 0 .8606675244077803 .5954652 0 0 1 14 .012144266 .3377397403399747 1 0 .8314157170778479 0 0 0 1 15 0 .42843334243252795 2 0 .8406463605192804 .5954652 0 0 1 15 .009230647 .5449415852219232 1 0 .8457498530453939 0 0 0 2 16 0 .641944955764613 2 0 .8683048852266039 .3317993 0 0 2 16 .02255503 .524244480400856 1 0 .7929118002416432 0 0 0 2 17 0 .6770883478172743 2 0 .8163368642780467 .3317993 0 0 2 17 .023425037 .5755950385517935 1 0 .8811443932411674 0 0 0 2 18 0 .6560495938435229 2 1 .9165220744168112 .3317993 0 0 2 18 .03537767 .7091292483254775 1 0 .6773241515002459 0 0 0 2 19 0 .85121412803532 2 0 .7589862514493954 .3317993 0 0 2 19 .08166207 .4849688681767829 1 0 .8204195205479452 0 0 0 2 20 0 .5811804708578187 2 0 .8416793893129771 .3317993 0 0 2 20 .02125984 .685989894350023 1 0 .7928177975148384 0 0 0 2 21 0 .8277890608586036 2 0 .828457731311777 .3317993 0 0 2 21 .03563996 .7121102248005802 1 0 .7838338895068595 0 0 0 2 22 0 .8619329388560157 2 0 .872473077649726 .3317993 0 0 2 22 .08863921 .9071300179748353 1 0 .8856816985436041 0 0 0 2 23 0 .9593705293276109 2 0 .9326021581461171 .3317993 0 0 2 23 .04692047 .5623674911660778 1 1 .8395382395382396 0 0 0 2 24 0 .6620594333102972 2 0 .8542088516054382 .3317993 0 0 2 24 .014670635 .5348067182412929 1 0 .9103541429696387 0 0 0 3 25 0 .6653963139734789 2 0 .915298976671581 .28208148 0 0 3 25 .004944839 .4125722543352601 1 0 .8892910634048926 0 0 0 3 26 0 .4892944388561575 2 0 .900830606594513 .28208148 0 0 3 26 .01153956 .5145569620253164 1 0 .868237347294939 0 0 0 3 27 0 .62026913372582 2 0 .8601643069393463 .28208148 0 0 3 27 -.008073069 .6256125821524903 1 0 .8756493401735875 0 0 0 3 28 0 .7158580413297394 2 0 .8784253184098804 .28208148 0 0 3 28 .0027759855 .4544952285283777 1 0 .8783187717363644 0 0 0 3 29 0 .5412363492612542 2 1 .8783167145512929 .28208148 0 0 3 29 -2.0720697e-06 .5304798962386511 1 0 .9205705009276438 0 0 0 3 30 0 .6460984702403908 2 0 .9102711397058824 .28208148 0 0 3 30 -.010299353 .43370756482224004 1 0 .9102380952380953 0 0 0 3 31 0 .5171763437963087 2 0 .9005827090022595 .28208148 0 0 3 31 -.009655378 .4417435328386157 1 0 .8575885377549252 0 0 0 3 32 0 .5016402405686168 2 0 .8635209235209235 .28208148 0 0 3 32 .005932394 .4869785664899747 1 0 .778960223307746 0 0 0 3 33 0 .5746084480303749 2 0 .7624526498389209 .28208148 0 0 3 33 -.016507579 .4162415833503367 1 0 .8761123713139068 0 0 0 3 34 0 .47278770253427505 2 1 .8665964542741794 .28208148 0 0 3 34 -.009515888 .559327566508895 1 0 .8404325464855598 0 0 0 3 35 0 .660734327400994 2 0 .8594414893617022 .28208148 0 0 3 35 .019008964 .5650262617035853 1 0 .9233479726279236 0 0 0 3 36 0 .7066111111111111 2 0 .9333808336302102 .28208148 0 0 3 36 .010032884 .6467490520994242 1 0 .9294468787705594 0 0 0 3 37 0 .7727925586485193 2 0 .9328652917946467 .28208148 0 0 3 37 .003418416 .43885714285714283 1 0 .8626991565135895 0 0 0 3 38 0 .4796839729119639 2 0 .8629751290473956 .28208148 0 0 3 38 .000275978 .5349692529496572 1 0 .8505993873465352 0 0 0 3 39 0 .6348095224320963 2 0 .8626212058616248 .28208148 0 0 3 39 .012021798 .569474921630094 1 0 .8865721434528774 0 0 0 3 40 0 .6965041965041965 2 0 .8881137465949106 .28208148 0 0 3 40 .001541624 .5593326906149139 1 0 .8820998278829604 0 0 0 3 41 0 .6688803780964798 2 0 .8722279220266751 .28208148 0 0 3 41 -.009871885 .24974731232197003 1 0 .8973921874433282 0 0 0 3 42 0 .30645011600928074 2 0 .9088443737344518 .28208148 0 0 3 42 .01145216 .3044498656702591 1 0 .8084917045579219 0 0 0 4 43 0 .44136020068534704 2 0 .7534060943451509 0 0 0 4 43 -.05508561 .06365623500559792 1 0 .8332165995447383 0 0 0 4 44 0 .12957372298031639 2 1 .753286551785397 0 0 0 4 44 -.07993005 .06817504100193827 1 0 .8357064790727029 0 0 0 4 45 0 .11110193633623715 2 0 .765450680404053 0 0 0 4 45 -.07025579 .2962797808638043 1 0 .7742774566473989 0 0 0 4 46 0 .5701609574907139 2 0 .7253514252245217 0 0 0 4 46 -.04892602 .15349887133182843 1 0 .8223345320244921 0 0 0 4 47 0 .3618196160925585 2 0 .7642843118005105 0 0 0 4 47 -.05805022 .07620412844036697 1 0 .8578691709844559 0 0 0 4 48 0 .16082134968218906 2 0 .7408955808864356 0 0 0 4 48 -.11697356 .12797713559860274 1 0 .8392732354996506 0 0 0 4 49 0 .20923184520340365 2 0 .7784266879037254 0 0 0 4 49 -.06084653 .1355679965983984 1 0 .8142646558566731 0 0 0 4 50 0 .26414204902576993 2 0 .7482440990213011 0 0 0 4 50 -.066020556 end
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