Graph combine formatting

Dear All,

I am trying to combine coefficient plots from 3 different regressions. My data looks as follows:

Code:

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(narc_nocod2 poly_all2 not_poly2) byte(event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28) long popestimate float(outcome qtr) byte stateFIPS
1.2464718  .9694781  .27699372 1 0 0 0 0 0 0  722038 2  2 2
 .9694781  .9694781          0 1 0 0 0 0 0 0  722038 2  1 2
3.7394154  3.323925   .4154906 1 0 0 0 0 0 0  722038 1  3 2
2.4929435 2.3544466  .13849686 1 0 0 0 0 0 0  722038 1  4 2
1.1079749 1.1079749          0 1 0 0 0 0 0 0  722038 2  3 2
 2.769937 2.4929435  .27699372 1 0 0 0 0 0 0  722038 1  1 2
 1.938956  1.938956          0 1 0 0 0 0 0 0  722038 2  4 2
 2.769937  2.769937          0 1 0 0 0 0 0 0  722038 1  2 2
 1.779849 1.6429377  .13691147 1 0 0 0 0 0 0  730399 1  7 2
 3.148964  2.875141  .27382293 1 0 0 0 0 0 0  730399 1  6 2
 1.506026  1.506026          0 1 0 0 0 0 0 0  730399 2  5 2
 2.053672 1.9167606  .13691147 1 0 0 0 0 0 0  730399 1  5 2
 .8214688  .4107344   .4107344 1 0 0 0 0 0 0  730399 2  6 2
2.4644065  2.053672   .4107344 1 0 0 0 0 0 0  730399 1  8 2
.54764587 .54764587          0 1 0 0 0 0 0 0  730399 2  7 2
 .6845573  .6845573          0 1 0 0 0 0 0 0  730399 2  8 2
2.1708307 2.1708307          0 1 0 0 0 0 0 0  737045 1  9 2
 .8140616  .8140616          0 0 1 0 0 0 0 0  737045 2 11 2
1.2210923 1.2210923          0 1 0 0 0 0 0 0  737045 1 10 2
 2.442185 2.3065078  .13567692 0 1 0 0 0 0 0  737045 1 12 2
.27135384 .27135384          0 1 0 0 0 0 0 0  737045 2  9 2
1.3567692 1.2210923  .13567692 1 0 0 0 0 0 0  737045 2 10 2
1.3567692 1.3567692          0 0 1 0 0 0 0 0  737045 2 12 2
 2.442185 2.1708307  .27135384 0 1 0 0 0 0 0  737045 1 11 2
2.1730065 1.9013808  .27162582 0 0 1 0 0 0 0  736307 1 16 2
 .8148775  .6790646  .13581291 0 0 1 0 0 0 0  736307 2 15 2
1.2223163 1.0865033  .13581291 0 0 1 0 0 0 0  736307 2 16 2
 .9506904  .9506904          0 0 1 0 0 0 0 0  736307 1 13 2
2.1730065  1.629755  .54325163 0 1 0 0 0 0 0  736307 1 14 2
 .6790646  .6790646          0 0 1 0 0 0 0 0  736307 2 13 2
2.4446325 2.3088195  .13581291 0 0 1 0 0 0 0  736307 1 15 2
1.0865033  .8148775  .27162582 0 1 0 0 0 0 0  736307 2 14 2
  .949092  .8135075  .13558458 0 0 0 1 0 0 0  737547 1 19 2
 .8135075  .8135075          0 0 0 1 0 0 0 0  737547 2 17 2
2.0337687  1.898184  .13558458 0 0 1 0 0 0 0  737547 2 18 2
 .8135075  .8135075          0 0 0 0 1 0 0 0  737547 2 19 2
2.7116916 2.7116916          0 0 0 0 1 0 0 0  737547 1 20 2
3.1184454 3.1184454          0 0 0 1 0 0 0 0  737547 1 17 2
 1.627015 1.4914304  .13558458 0 0 1 0 0 0 0  737547 1 18 2
.40675375 .40675375          0 0 0 0 1 0 0 0  737547 2 20 2
  2.56236  2.427499  .13486104 0 0 0 1 0 0 0  741504 1 21 2
1.4834714  .9440272  .53944415 0 0 0 0 0 0 0  741504 1 24 2
 2.966943   2.56236   .4045831 0 0 0 0 0 0 0  741504 1 23 2
1.2137494 1.2137494          0 0 0 0 0 0 0 0  741504 2 24 2
 .6743052  .6743052          0 0 0 0 0 0 0 0  741504 2 23 2
1.3486104 1.2137494  .13486104 0 0 0 1 0 0 0  741504 1 22 2
1.0788883 1.0788883          0 0 0 0 1 0 0 0  741504 2 22 2
1.6183325 1.4834714  .13486104 0 0 0 1 0 0 0  741504 2 21 2
2.1627877 2.0276134  .13517423 0 0 0 0 0 0 0  739786 1 25 2
 .8110453  .8110453          0 0 0 0 0 1 0 0  739786 1 27 2
2.7034845 2.7034845          0 0 0 0 0 0 0 0  739786 1 26 2
1.3517423  1.216568  .13517423 0 0 0 0 0 0 0  739786 2 25 2
 .9462196  .9462196          0 0 0 0 0 1 0 0  739786 2 27 2
1.4869165 1.4869165          0 0 0 0 0 0 0 0  739786 2 26 2
1.2919805  1.271142 .020838395 0 0 0 0 0 0 0 4798834 2  3 1
2.5006075  2.104678   .3959295 0 0 0 0 0 0 0 4798834 1  2 1
 1.312819  1.271142  .04167679 0 0 0 0 0 0 0 4798834 2  2 1
2.2713852 1.9796475  .29173753 0 0 0 0 0 0 0 4798834 1  4 1
 2.646476 2.2713852   .3750911 0 0 0 0 0 0 0 4798834 1  1 1
2.2922235 2.1463547  .14586876 0 0 0 0 0 0 0 4798834 1  3 1
1.0835966  .9377278  .14586876 0 0 0 0 0 0 0 4798834 2  4 1
1.3336573  1.208627  .12503037 0 0 0 0 0 0 0 4798834 2  1 1
 2.554218  2.138898     .41532 0 0 0 0 0 0 0 4815564 1  8 1
 2.761878  2.263494    .498384 0 0 0 0 0 0 0 4815564 1  6 1
 2.637282 2.3257918     .31149 0 0 0 0 0 0 0 4815564 1  7 1
 1.515918   1.45362    .062298 0 0 0 0 0 0 0 4815564 2  8 1
 1.370556  1.225194  .14536199 0 0 0 0 0 0 0 4815564 2  5 1
  1.55745   1.45362     .10383 0 0 0 0 0 0 0 4815564 2  7 1
  1.34979  1.266726    .083064 0 0 0 0 0 0 0 4815564 2  6 1
  2.18043  1.889706  .29072398 0 0 0 0 0 0 0 4815564 1  5 1
 1.594051  1.573349  .02070196 0 0 0 0 0 0 0 4830460 2 12 1
1.9252825 1.5319452   .3933373 0 0 0 0 0 0 0 4830460 1 12 1
1.2835217 1.2214158  .06210589 0 0 0 0 0 0 0 4830460 2 11 1
 2.649851  2.132302  .51754904 0 0 0 0 0 0 0 4830460 1  9 1
2.1530042 1.9459845  .20701963 0 0 0 0 0 0 0 4830460 1 10 1
1.3249255 1.2628196  .06210589 0 0 0 0 0 0 0 4830460 2 10 1
1.3456275 1.1800119   .1656157 0 0 0 0 0 0 0 4830460 2  9 1
  2.21511 1.8631766   .3519334 0 0 0 0 0 0 0 4830460 1 11 1
1.7965997 1.4042388   .3923609 0 0 0 0 0 0 0 4842481 1 13 1
 2.127009 2.0031054  .12390343 0 0 0 0 0 0 0 4842481 1 15 1
1.7139975 1.4868412   .2271563 0 0 0 0 0 0 0 4842481 1 14 1
1.5694435 1.5074917  .06195172 0 0 0 0 0 0 0 4842481 2 14 1
1.3422872  1.300986  .04130114 0 0 0 0 0 0 0 4842481 2 16 1
1.6520457 1.3216366   .3304091 0 0 0 0 0 0 0 4842481 1 16 1
1.5074917 1.3216366  .18585515 0 0 0 0 0 0 0 4842481 2 13 1
 1.548793 1.5281423  .02065057 0 0 0 0 0 0 0 4842481 2 15 1
 1.256913 1.2157028  .04121026 0 0 0 0 0 0 0 4853160 2 20 1
 .9684412  .9066258   .0618154 0 0 0 0 0 0 0 4853160 2 18 1
1.0714668 1.0508617  .02060513 0 0 0 0 0 0 0 4853160 2 17 1
 1.730831  1.545385   .1854462 0 0 0 0 0 0 0 4853160 1 18 1
 1.236308 1.1950977  .04121026 0 0 0 0 0 0 0 4853160 2 19 1
1.6072003 1.4835695   .1236308 0 0 0 0 0 0 0 4853160 1 19 1
1.6072003  1.380544  .22665645 0 0 0 0 0 0 0 4853160 1 20 1
1.3187284 1.1332822   .1854462 0 0 0 0 0 0 0 4853160 1 17 1
1.0072471  .9661349  .04111212 0 0 0 0 0 0 0 4864745 2 24 1
1.1100273 1.0689152  .04111212 0 0 0 0 0 0 0 4864745 2 23 1
 1.377256  1.336144  .04111212 0 0 0 0 0 0 0 4864745 2 22 1
1.7472652 1.5417047  .20556062 0 0 0 0 0 0 0 4864745 1 24 1
1.4389243 1.2744758   .1644485 0 0 0 0 0 0 0 4864745 1 23 1
1.0278031  .9661349  .06166819 0 0 0 0 0 0 0 4864745 2 21 1
end

I estimate the regressions, coefficient plots and combine them as follows:

Code:

local controls  treatMA qavg_pct_lf_unemp qavg_pct_lf_unemp_miss pct_lhs pct_lhs_miss pct_hs pct_hs_miss  ///
perc_black perc_black_miss perc_nonwhite perc_nonwhite_miss pctmale  pctmale_miss pctover65 pctover65_miss ///  // perfect
state_share_rural_2010 md_100000 pa_100000 rn_100000 state_share_rural_2010_miss md_100000_miss pa_100000_miss rn_100000_miss


quietly eststo : reghdfe narc_nocod2 event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28 ///
`controls' [weight=popestimate] if outcome==2, absorb(i.qtr i.stateFIPS i.stateFIPS#(c.qtr c.qtrsq)) vce(cluster stateFIPS)

    graph drop a
       coefplot, vertical keep(event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28) yline(0)  ///
        title("(1) Severe poisoning calls") subtitle("(per 100,000 persons)")  ///
        ytitle("Severe poisonings/ 100,000 persons", margin(vlarge)) xtitle("Years relative to must-access PDMP adoption") graphregion(color(white)) levels(95) grid(none) ///
        coeflabels(event_qtr21="5 years prior" event_qtr22="4 years prior" event_qtr23="3 years prior" event_qtr24="2 year prior" ///
        event_qtr26="year after" event_qtr27="2 years after" event_qtr28="3 years after",  angle(45)) name(a)

 
quietly eststo : reghdfe poly_all2 event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28 ///
`controls' [weight=popestimate] if outcome==2, absorb(i.qtr i.stateFIPS i.stateFIPS#(c.qtr c.qtrsq)) vce(cluster stateFIPS)

     graph drop b
       coefplot, vertical keep(event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28) yline(0)  ///
        title("(2) Poly-drug severe poisoning calls") subtitle("(per 100,000 persons)")  ///
        ytitle("Poly-drug severe poisonings", margin(vlarge)) xtitle("Years relative to must-access PDMP adoption") graphregion(color(white)) levels(95) grid(none) ///
        coeflabels(event_qtr21="5 years prior" event_qtr22="4 years prior" event_qtr23="3 years prior" event_qtr24="2 year prior" ///
        event_qtr26="year after" event_qtr27="2 years after" event_qtr28="3 years after",  angle(45)) name(b)

 
 quietly eststo : reghdfe not_poly2 event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28 ///
`controls' [weight=popestimate] if outcome==2, absorb(i.qtr i.stateFIPS i.stateFIPS#(c.qtr c.qtrsq)) vce(cluster stateFIPS)
 
     graph drop c
       coefplot, vertical keep(event_qtr21 event_qtr22 event_qtr23 event_qtr24 event_qtr26 event_qtr27 event_qtr28) yline(0)  ///
        title("(3) Single-drug severe poisoning calls") subtitle("(per 100,000 persons)")  ///
        ytitle("Single-drug severe poisonings", margin(vlarge)) xtitle("Years relative to must-access PDMP adoption") graphregion(color(white)) levels(95) grid(none) ///
        coeflabels(event_qtr21="5 years prior" event_qtr22="4 years prior" event_qtr23="3 years prior" event_qtr24="2 year prior" ///
        event_qtr26="year after" event_qtr27="2 years after" event_qtr28="3 years after",  angle(45)) name(c)

 graph combine a b c, row(1) col(3) iscale(.5) graphregion(margin(l=15 r=10)) ysize(11) xsize(9.5)

Please find attached the resulting graph. I know attachments are discouraged but I am unable to find a way to show the output otherwise.

How can I change the orientation from portrait to landscape so as to make the graphs better spaced? Right now they look really elongated and are hard to read.

I will greatly appreciate any help in formatting the combined graph better.

Sincerely,
Sumedha.

Share on FacebookPlus on Google+