coefplot : groups() option not producing desired results

[Stephen Okiya]

Hi Stata users,
I am using coefplot in Stata 15 to try and replicate the graph below where there are labels for different coefficients on the left.

The code runs successfully but the labels aren’t drawn.

Example of data am using is below

* Example generated by -dataex-. To install: ssc install dataex
clear
input double(gr1_v1 gr1_v3 gr1_v4) byte gr2_v1 double(gr2_v2 ctr3 ctr2 ctr5) int ctr4 byte gr1_v2 double(ctr1 dep)
-.6599468 .899                . 0 31.1           58.319  3.266513294718 25.5  460  7 4.01296965034928  1.01532756627686
 .0217204 .729 75.0666666666667 0 40.7            72.95  2.654591643397 28.2  505  9 7.39194513263972  1.10688086439221
 1.208909 .128                . 0 60.3 81.1243902439025 4.0700396132298 50.5 1844  0 21.9561365414532  4.90884672095601
 1.002136 .025 21.0076857386849 0 65.9 83.3292682926829 4.1766247543894   83 2322  1 19.3798772302397  6.36412555386142
 .3499596 .719 53.8528896672504 0 73.2           76.683  2.537743924381   81  496  8 11.9009501051758  .599379329093928
 1.084034 .071 39.7115351934217 0 58.3           79.909 3.3414406424637 72.7 1171  3 11.5299351385754  3.93969045852249
 .3403786 .688 47.9964902018134 0 54.8           63.538  3.494744343401 81.5  576  8 5.31785410434149  2.44881843884806
 1.887119 .022                . 0 64.6  82.509756097561 4.5896387574232 58.6 5281  2 17.0491024330957  3.81613775512702
 .4873109 .192 16.6160081053698 0   54 76.0634146341464 2.7878603854949 55.5 1293  0 19.1578000000818  3.98688878065147
-1.457285 .581                . 0 32.3            64.13  3.888609794346 44.8    8 20 2.58482735006572    2.030489676202
-.5659866 .385                . 0 28.8           61.174  2.790786304386 24.2   17 10 3.25357804338301  .232070929491975
 1.480526 .052                . 0 68.2 82.5243902439024 4.3359284092312 75.3 3964  1 20.0350636225599   6.0631190563328
 -.568605 .919                . 0 39.2           69.289  3.093067878339 57.7   50 10 4.56857986788513                 0
 1.850466 .026 34.5835631549917 0 75.6 81.5609756097561 4.2323386934973   86 4252  0 19.1964320948507  5.84410294800882
-.6115379 .829 57.9370395177495 0 49.3             71.2  1.890168286892 64.7   94 12 4.49463845131904  1.26144642965273
-.6234712 .449                . 0 34.2            61.44  1.818830837499 36.9   14 15 2.58992799444937  .363654340665717
 .6626508 .138 17.6724137931034 0 55.4 77.8512195121951 2.8154505203677 61.7 1244  0 17.5172687114464  3.35607047107291
 .3234982 .632                . 1 49.3           74.874  3.468560666431 74.4 2114  8 3.31359274838029   2.6803724019718
 .4569183 .401                . 0 53.3 77.8268292682927 2.7646862730083 72.3 1334  2 20.4465533534434   3.2656320131974
 -2.19103 .808                . 0 16.6           56.709  3.400798436406 21.5    . 20 2.87330473821098  1.75740818499543
-1.554787 .766                . 0 26.5           60.026  3.852251229028 25.1    4 24 3.01784062159803  .599255783985903
-1.068652 .425                . 0 43.4           66.558   3.22893746746 59.2   58 18 5.78468598810298  .105903309510554
-.7286705 .643                . 0   28           63.279  3.803750090162 23.3   32 13 2.64539308279661  .199233471764191
-.8742813 .707                . 0 28.1           59.309  2.787749626316 29.3   33 11 2.89079230574002 .0656059745175615
-1.097704 .887                . 0 32.3           70.647  1.605546963219 24.1   60 11  3.0218758999859  1.81878434488838
 1.043452 .143                . 0 62.9 74.6804878048781  3.062378374171 97.3  868  0 20.0437012952645    2.599236926728
-.8024699  .76 20.9441464050046 0 43.1           74.068 3.1349399700806 39.9  297  7 5.24747224234179  1.85837971028276
 1.596495 .041  31.767955801105 0 75.5 82.4975609756098 3.8827269902903 97.3 3094  2 15.6567740028615  1.62586765721305
 .8301269    .                . 0    .                .               .    .    .  .                .                 .
-.4302173 .693                . 0 37.7           76.271  3.577294022314 37.7  853  9 6.18465081086714  4.55230246460259
-.6820061 .737 16.2442103529089 0 32.7            73.81   3.28682451749   50  172  8 4.81210741748212   1.8274571050858
-.2092959 .648 47.6702508960573 0 43.7           76.218   3.77476883394 56.8  218  7 7.01285998016383  1.88806509478269
 .6312364 .533 83.5707502374169 0 41.2           79.981  3.408640114945 32.7 3205  3 1.36989305372263  2.63489390958162
-.4152199 .463 24.8666666666667 0   38 71.7809756097561  3.265953556417 36.5  227  9  16.434413962673  2.80925249570885
 .2830485 .402 50.3917860037828 0 46.5           69.165  3.018352798177 47.4   61 11 6.17995757333666  1.54224992948802
  .112718 .471 55.5555555555556 0 42.1           74.292  2.697290824098 42.9  313  7 3.84666107741343  .643944595030249
 1.125806 .115 7.98076923076923 0 67.2 81.1756097560976 2.7736630289271 73.7 2004  0 19.6069808775183  3.97172390436354
-1.022591 .811 36.2706083001706 0 37.8            53.95  2.097026014282 44.6   28 18 2.74737722689511  .846933888122284
-.7266325 .757                . 0 27.5           64.464  2.843522294086 39.5   60 16 3.14108516780183  1.71236057288775
 1.182665 .079  49.874686716792 1 70.2 82.6268292682927 3.6666145367932 92.1 1604  0 14.4185012031302  1.82656471855618
 1.716108 .034                . 1 75.3 82.2489756097561 4.2290833128677 96.4 3465  0 17.2323560257884   5.2434788559126
-.4002573  .96 22.2787385554425 0 38.3           73.689  3.039886524686 37.1  428  3 7.08287675970026  3.84844519339733
 1.675817  .03 27.4238227146814 0 59.8  84.099756097561 3.7491687516534 70.1 3839  1 27.5771763175428   2.0797342180702
-.7562658 .172                . 0 36.4           64.479  3.701542401593   42   45 10 2.60131742500686  .316910909325943
 .1902379 .141 36.6982124079916 0 36.6           73.245 3.2898275146162 14.7 1151  3 10.7346218102857  1.91042858698441
-.9023383 .675                . 0 35.1           70.169  3.230997207665   22   29  9 5.72755051459756  .193603785720567
-.4439246 .627 38.7619047619048 0 23.6           76.499  3.589836161482   12  676 11 6.36249574901306  2.77933499954802
-.5172144 .613 27.2790265899743 0 35.7           73.992 3.3022770624888 34.6  396  8 6.43021038744429  .948313471566443
 1.871631 .016                . 0 70.4 81.0048780487805 4.2207698434522   86 4284  0  19.812929220959  4.59550973875025
end

The code is below

    use "data.dta", clear
    
    global controls ctr1 ctr2 ctr3 ctr4 ctr5 

    foreach var in gr1_v1 gr1_v2 gr1_v3 gr1_v4 {
        preserve
        center dep `var', inplace standardize
        regress dep `var', noconstant
        estimates store g1_b_`var'
        restore
    }

    foreach var in gr1_v1 gr1_v2 gr1_v3 gr1_v4 {
        preserve
        center dep `var' $controls, inplace standardize
        regress dep `var' $controls, noconstant
        estimates store g1_c_`var'
        restore
    }

    
    foreach var in gr2_v1 gr2_v2 {
        preserve
        center dep `var', inplace standardize
        regress dep `var', noconstant
        estimates store g2_b_`var'
        restore
    }

    foreach var in gr2_v1 gr2_v2 {
        preserve
        center dep `var' $controls, inplace standardize
        regress dep `var' $controls, noconstant
        estimates store g2_c_`var'
        restore
    }


    coefplot (*_b_*, label(Bivariate) pstyle(p3)) (*_c_*, label(With Controls) pstyle(p4)), ///
        bylabel(Price) msymbol(S) drop(_cons $controls) xline(0) coeflabels(, labsize(vsmall)) ///
        legend( size(vsmall)) ///
        groups(g1_b_? g1_c_? = "Group 1" g2_b_? g2_c_? = "Group 4")

Thanks in advance!

[Ben Jann]

g1_b_?, g1_c_?, g2_b_?, and g2_c_? do not refer to any coefficients in the model. Maybe this is what you want:

coefplot (*_b_*, label(Bivariate) pstyle(p3)) (*_c_*, label(With Controls) pstyle(p4)), ///
    bylabel(Price) msymbol(S) drop(_cons $controls) xline(0) coeflabels(, labsize(vsmall)) ///
    legend( size(vsmall)) ///
    groups(gr1_* = "Group 1" gr2_* = "Group 4")

[Stephen Okiya]

Thanks so much Ben Jann !! This is really what I want. I sincerely appreciate the help.