Correlations table with groups of variables in the rows

[Giorgio Di Stefano]

Hello,

I'm trying to make a correlation table with cpcorr by @Nick Cox.
I have no problem implementing the code; what I would like, however, is to create groups of variables in the rows, such as group A and from below the variables, group B and from below the variables, using their labels, and to export to Latex in horizontal order.

Also, I would like, in addition to the correlations, to display the covariance and P-values in the same cell with a note at the bottom of the table noting correlations, covariance, and the p values

I am using the following code, and sample data is provided below.

cpcorr fd ka ext dom pr la \ type1 type2 indicator1 decade1 decade2 decade3

* Example generated by -dataex-. For more info, type help dataex
clear
input float(id year) str97 country str1 group float(fd ka ext dom pr la type1 type2 indicator1 decade) byte(decade1 decade2 decade3)
1 1992 "Country1" "A"   .524175   2.321955  .75 .7777778 .071428575        1 0 1       12.2 1990 1 0 0
1 1993 "Country1" "A"  .5846328   2.321955  .75 .7777778 .071428575        1 0 1  17.553352 1990 1 0 0
1 1994 "Country1" "A"  .6478685   2.321955  .75 .9444444 .071428575 .7912164 0 1      19.11 1990 1 0 0
1 2000 "Country1" "A"  .8414965   1.048859  .75        1  .53571427 .7782844 0 1     28.634 2000 0 1 0
1 2001 "Country1" "A"   .873997   1.048859  .75        1   .6190476 .7782844 0 1   26.41307 2000 0 1 0
1 2002 "Country1" "A"  .8985876   1.048859  .75        1   .6190476 .7661784 0 1   5.536341 2000 0 1 0
1 2003 "Country1" "A"  .9015374   1.048859  .75        1   .6190476 .7661784 0 1   5.536341 2000 0 1 0
1 2004 "Country1" "A"  .9041975   1.048859  .75        1   .6190476 .7661784 0 1   7.350179 2000 0 1 0
1 2010 "Country1" "A"   .941813   1.048859 .875        1   .8452381 .7704133 0 1   6.241802 2010 0 0 1
1 2011 "Country1" "A"   .934702   1.048859 .875        1   .8452381 .7704133 0 1      5.068 2010 0 0 1
1 2012 "Country1" "A"  .9079577   1.303478 .875        1   .8452381 .7704133 0 1      5.068 2010 0 0 1
1 2013 "Country1" "A"  .8901507  1.5580974 .875        1   .8452381 .7694158 0 1   7.929047 2010 0 0 1
2 1992 "Country2" "A"   .399736   .6099069 .875 .7777778          0 .5697657 0 1        1.6 1990 1 0 0
2 1993 "Country2" "A"   .461959  2.0673358 .875 .9444444          0 .5697657 0 1   6.996447 1990 1 0 0
2 1994 "Country2" "A"  .4953545   2.321955 .875 .9444444          0 .5697657 0 1    8.69136 1990 1 0 0
2 2000 "Country2" "A"  .7018992   2.321955    1        1   .4404762 .5697657 0 1   2.364474 2000 0 1 0
2 2001 "Country2" "A"  .7035186   2.321955    1        1   .5952381 .5697657 0 1   2.364474 2000 0 1 0
2 2002 "Country2" "A"  .6993845   2.321955    1        1   .5952381 .5457992 0 1  -.7668521 2000 0 1 0
2 2003 "Country2" "A"  .7077955   2.321955    1        1   .5952381 .5457992 0 1 -2.9592714 2000 0 1 0
2 2004 "Country2" "A"   .728983   2.321955    1        1   .5952381 .5457992 0 1  -2.950783 2000 0 1 0
2 2010 "Country2" "A"  .7894757   2.321955    1 .9444444   .9166667 .5718316 0 1      3.891 2010 0 0 1
2 2011 "Country2" "A"  .8007692   2.321955    1 .9444444   .9166667 .5718316 0 1      3.891 2010 0 0 1
2 2012 "Country2" "A"  .7593077   2.321955    1 .9444444   .9166667 .5718316 0 1 -2.5410414 2010 0 0 1
2 2013 "Country2" "A"  .7435991   2.321955    1 .9444444   .9166667 .5718316 0 1  -6.333579 2010 0 0 1
3 1992 "Country3" "B"  .5840359   2.321955    1 .7777778  .08333334 .6281998 0 1   .3835026 1990 1 0 0
3 1993 "Country3" "B"  .6147648   2.321955    1 .8888889  .08333334 .6281998 0 1   .3835026 1990 1 0 0
3 1994 "Country3" "B"   .632942   2.321955    1 .8888889  .08333334 .6260909 0 1   .8169867 1990 1 0 0
3 2000 "Country3" "B"  .7692201   2.321955    1 .8888889        .75 .6297867 0 1  1.9049623 2000 0 1 0
3 2001 "Country3" "B"  .7502941   2.321955    1 .8888889        .75 .6297867 0 1  1.9049622 2000 0 1 0
3 2002 "Country3" "B"  .7244223   2.321955    1 .8888889   .8333333 .6297867 0 1   1.283737 2000 0 1 0
3 2003 "Country3" "B"  .7401305   2.321955    1 .8888889   .8333333 .6297867 0 1 -1.3254085 2000 0 1 0
3 2004 "Country3" "B"  .7518873   2.321955    1 .8888889   .8333333 .6547069 0 1 -1.3254085 2000 0 1 0
3 2010 "Country3" "B"  .7356597   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2011 "Country3" "B"  .7201834   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2012 "Country3" "B"  .7283527   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2013 "Country3" "B"  .7077386   2.321955    1 .9444444          1 .6547069 0 1  1.1165322 2010 0 0 1
4 1992 "Country4" "B"  .3452282   .6099069 .875 .5555556 .071428575 .6121462 0 1   2.615249 1990 1 0 0
4 1993 "Country4" "B"  .3790323  2.0673358    1 .7222222 .071428575 .6121462 0 1  1.4437795 1990 1 0 0
4 1994 "Country5" "C"  .4175321   2.321955    1 .7222222 .071428575 .6121462 0 1  4.0116615 1990 1 0 0
4 2000 "Country5" "C"   .759881   2.321955    1 .8888889   .7619048 .6121462 0 1    5.97681 2000 0 1 0
4 2001 "Country5" "C"  .7410694   2.321955    1 .8888889   .7619048 .6121462 0 1   7.402936 2000 0 1 0
4 2002 "Country5" "C"  .7281089   2.321955    1 .8888889   .8333333 .6121462 0 1      8.534 2000 0 1 0
4 2003 "Country5" "C"   .735869   2.321955    1 .8888889   .8333333 .6263371 0 1      8.534 2000 0 1 0
4 2004 "Country5" "C"  .7334849   2.321955    1 .8888889   .8333333 .6263371 0 1      8.534 2000 0 1 0
4 2010 "Country5" "C"  .7798166   2.321955    1 .9444444   .9166667 .6263371 0 1     -16.25 2010 0 0 1
4 2011 "Country5" "C"  .7637033   2.321955    1 .9444444   .9166667 .6263371 0 1 -14.330358 2010 0 0 1
4 2012 "Country5" "C"  .7608096   2.321955    1 .9444444   .9166667 .6263371 0 1          0 2010 0 0 1
4 2013 "Country5" "C"  .7455279   2.321955    1        1   .9166667  .607849 0 1   .6806767 2010 0 0 1
5 1992 "Country6" "C"  .1757301          .    .        .          .        . 0 1          . 1990 1 0 0
5 1993 "Country6" "C"  .1761862          .    .        .          .        . 1 0          . 1990 1 0 0
5 1994 "Country6" "C"  .1562944          .    .        .          .        . 1 0          . 1990 1 0 0
5 2000 "Country6" "C"  .2008834 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2001 "Country6" "C" .17261477 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2002 "Country6" "C" .21249928 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2003 "Country6" "C"  .2206576 -.02334493    .        .          .        . 1 0          . 2000 0 1 0
5 2004 "Country6" "C" .23541167 -.02334493    .        .          .        . 1 0          . 2000 0 1 0
5 2010 "Country6" "C" .27683625   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2011 "Country6" "C" .27487376   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2012 "Country6" "C" .27767062   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2013 "Country6" "C"  .2884341   1.249751    .        .          .        . 0 1          . 2010 0 0 1
6 1992 "Country7" "C" .25534174  -.1539507 .625       .5          0 .8271327 1 0          . 1990 1 0 0
6 1993 "Country7" "C" .28078705  -.1539507 .625       .5  .16666667 .8271327 1 0          . 1990 1 0 0
6 1994 "Country7" "C"  .3567602  -.1539507 .625 .5555556  .16666667 .8271327 1 0          . 1990 1 0 0
6 2000 "Country7" "C"  .4190661 -1.2261546 .625 .6111111  .23809524 .8271327 0 1          . 2000 0 1 0
6 2001 "Country7" "C"  .3738855 -1.2261546 .625 .6666667   .3928571 .8271327 0 1          . 2000 0 1 0
6 2002 "Country7" "C"   .404098 -1.2261546 .625 .6666667   .3928571 .8271327 0 1          . 2000 0 1 0
6 2003 "Country7" "C"  .4157713 -1.2261546 .875 .6666667   .3928571 .7653575 0 1          . 2000 0 1 0
6 2004 "Country7" "C"  .4085605 -1.2261546 .875 .6666667  .53571427 .7653575 0 1          . 2000 0 1 0
6 2010 "Country7" "C"  .4888775 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2011 "Country7" "C"  .4789392 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2012 "Country7" "C"  .4922497 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2013 "Country7" "C"   .508882 -.02334493  .75 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
7 1992 "Country8" "D" .56565696   2.321955    1 .9444444   .7738096 .8009957 0 1  13.403038 1990 1 0 0
7 1993 "Country8" "D"  .6403931   2.321955    1 .9444444   .7738096 .8070084 0 1       12.1 1990 1 0 0
7 1994 "Country8" "D"  .6921942   2.321955    1 .9444444   .8452381 .8070084 0 1       12.1 1990 1 0 0
7 2000 "Country8" "D"  .8552948   2.321955    1        1   .9285714 .8314556 0 1      1.806 2000 0 1 0
7 2001 "Country8" "D"  .8805222   2.321955    1        1   .9285714 .8314556 0 1   1.958802 2000 0 1 0
7 2002 "Country8" "D"  .8265579   2.321955    1        1   .9285714 .8314556 0 1      2.076 2000 0 1 0
7 2003 "Country8" "D"  .8580942   2.321955    1        1          1 .8314556 0 1      2.076 2000 0 1 0
7 2004 "Country8" "D"  .8708485   2.321955    1        1          1 .8314556 0 1      2.076 2000 0 1 0
7 2010 "Country8" "D"  .8683383   2.321955    1        1          1 .8314556 0 1   3.564247 2010 0 0 1
7 2011 "Country8" "D"  .8672714   2.321955    1 .9444444          1 .8314556 0 1   5.454876 2010 0 0 1
7 2012 "Country8" "D"  .8684435   2.321955    1 .8888889          1 .8429364 0 1   5.454876 2010 0 0 1
7 2013 "Country8" "D"  .8866873   2.321955    1 .9444444          1 .8429364 0 1   5.454876 2010 0 0 1
8 1992 "Country8" "D"  .5748482   2.321955    1 .8888889  .52380955 .9702252 0 1       14.9 1990 1 0 0
8 1993 "Country8" "D"  .6702072   2.321955    1 .8888889  .52380955 .9702252 0 1   .0375137 1990 1 0 0
8 1994 "Country8" "D"  .6812267   2.321955    1 .8888889  .52380955 .9702252 0 1      -.781 1990 1 0 0
8 2000 "Country8" "D"  .8790284   2.321955    1        1        .75 .9702252 0 1      1.463 2000 0 1 0
8 2001 "Country8" "D"   .889005   2.321955    1        1        .75 .9702252 0 1   5.542341 2000 0 1 0
8 2002 "Country8" "D"  .8849987   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2003 "Country8" "D"  .8916724   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2004 "Country8" "D"  .8910962   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2010 "Country8" "D"  .8951228   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2011 "Country8" "D"  .8785759   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2012 "Country8" "D"  .8894278   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2013 "Country8" "D"  .8901961   2.321955    1        1   .8333333 .9702252 0 1   1.298654 2010 0 0 1
end

[Nick Cox]

Your needs go far beyond what cpcorr can do, so the problem is wide open.

[Giorgio Di Stefano]

Your needs go far beyond what cpcorr can do, so the problem is wide open.

Any ideas how to address that?

[Nick Cox]

The new table command is highly flexible. All I can guess is that it may get you closer to what you want than cpcorr will. I have no ambitions to extend the scope of cpcorr (from SSC, given that people may be wondering). Your table is quite easy to specify verbally but you will need custom code to get there.

[Jeff Pitblado (StataCorp)]

If you have Stata 17 or newer, you can use the collect with
cpcorr to build your table for LaTeX. One challenge here is that
cpcorr does not apply the same row and column names of
r(C) to r(p), so I had to write a short (byable)
wrap-around program to accomplish this. Also the example data does not
have labels on the variables, but if it did, then those labels would
show up in the table instead of the variable names.

Here is the code I used.

program mod_cpcorr, rclass byable(recall)
    syntax anything [if] [in] [, *]
    marksample touse
    cpcorr `anything' if `touse', `options'
    tempname C p
    matrix `C' = r(C)
    matrix `p' = r(p)
    matrix colname `p' = `:colfullname `C', quote'
    matrix rowname `p' = `:rowfullname `C', quote'
    return scalar N = r(N)
    return matrix C = `C'
    return matrix p = `p'
end

sort group

by group : ///
    collect corr=(r(C)) pvalue=(r(p)) : ///
    mod_cpcorr fd ka ext dom pr la \ ///
        type1 type2 indicator1 decade1 decade2 decade3
by group : ///
    collect cov=(r(C)) : ///
    mod_cpcorr fd ka ext dom pr la \ ///
        type1 type2 indicator1 decade1 decade2 decade3, covariance

* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[pvalue] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov pvalue, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (group#rowname) (colname#result[show])

collect export table.tex, replace

Here is the table.

. collect layout (group#rowname) (colname#result[show])

Collection: default
      Rows: group#rowname
   Columns: colname#result[show]
   Table 1: 28 x 6

---------------------------------------------------------------------------------------------------------------------
      |          type1          type2          indicator1             decade1             decade2             decade3
------+--------------------------------------------------------------------------------------------------------------
A     |
  fd  | . (0.00) 1.000 . (0.00) 1.000   0.06 (0.08) 0.798 -0.83 (-0.06) 0.000   0.29 (0.02) 0.175   0.47 (0.04) 0.022
  ka  | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-1.69) 0.150   0.19 (0.05) 0.386 -0.15 (-0.05) 0.490 -0.02 (-0.00) 0.943
  ext | . (0.00) 1.000 . (0.00) 1.000 -0.76 (-0.72) 0.000 -0.37 (-0.02) 0.073 -0.04 (-0.00) 0.846   0.39 (0.02) 0.063
  dom | . (0.00) 1.000 . (0.00) 1.000 -0.12 (-0.08) 0.578 -0.76 (-0.02) 0.000   0.52 (0.02) 0.009   0.16 (0.01) 0.456
  pr  | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-1.01) 0.096 -0.91 (-0.13) 0.000   0.10 (0.02) 0.648   0.73 (0.12) 0.000
  la  | . (0.00) 1.000 . (0.00) 1.000   0.65 (0.79) 0.001   0.26 (0.02) 0.214 -0.15 (-0.01) 0.485 -0.09 (-0.01) 0.692
B     |
  fd  | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.06) 0.198 -0.82 (-0.06) 0.000   0.52 (0.04) 0.058   0.32 (0.02) 0.261
  ka  | . (0.00) 1.000 . (0.00) 1.000 -0.46 (-0.24) 0.096 -0.43 (-0.10) 0.127   0.24 (0.05) 0.413   0.20 (0.04) 0.490
  ext | . (0.00) 1.000 . (0.00) 1.000 -0.44 (-0.02) 0.114 -0.37 (-0.01) 0.190   0.21 (0.00) 0.478   0.18 (0.00) 0.549
  dom | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-0.04) 0.222 -0.67 (-0.04) 0.008   0.20 (0.01) 0.497   0.50 (0.03) 0.066
  pr  | . (0.00) 1.000 . (0.00) 1.000 -0.15 (-0.07) 0.621 -0.98 (-0.20) 0.000   0.38 (0.08) 0.185   0.64 (0.12) 0.014
  la  | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-0.01) 0.296 -0.70 (-0.01) 0.005 -0.04 (-0.00) 0.881   0.79 (0.01) 0.001
C     |
  fd  | . (0.00) 1.000 . (0.00) 1.000 -0.23 (-0.23) 0.525 -0.99 (-0.03) 0.000   0.23 (0.01) 0.524   0.37 (0.02) 0.291
  ka  | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000 -0.40 (-0.27) 0.254 -0.85 (-0.02) 0.002 -0.16 (-0.01) 0.659   0.69 (0.03) 0.028
  pr  | . (0.00) 1.000 . (0.00) 1.000 -0.27 (-0.64) 0.451 -0.97 (-0.08) 0.000   0.12 (0.02) 0.745   0.47 (0.06) 0.166
  la  | . (0.00) 1.000 . (0.00) 1.000 -0.42 (-0.03) 0.228 -0.29 (-0.00) 0.414 -0.13 (-0.00) 0.721   0.31 (0.00) 0.382
D     |
  fd  | . (0.00) 1.000 . (0.00) 1.000 -0.62 (-0.31) 0.001 -0.96 (-0.05) 0.000   0.44 (0.02) 0.030   0.42 (0.02) 0.040
  ka  | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.07) 0.077 -0.73 (-0.01) 0.000   0.60 (0.01) 0.002   0.04 (0.00) 0.858
  pr  | . (0.00) 1.000 . (0.00) 1.000 -0.16 (-0.11) 0.467 -0.65 (-0.04) 0.001   0.16 (0.01) 0.467   0.43 (0.03) 0.035
  la  | . (0.00) 1.000 . (0.00) 1.000 -0.34 (-0.11) 0.107 -0.09 (-0.00) 0.687   0.03 (0.00) 0.899   0.05 (0.00) 0.813
---------------------------------------------------------------------------------------------------------------------
Correlations, (covariances), and p-values.

This table is rather wide, but you can use collect layout to select
columns and export them separately. For example

. collect layout (group#rowname) (colname[type1 type2]#result[show])

Collection: default
      Rows: group#rowname
   Columns: colname[type1 type2]#result[show]
   Table 1: 28 x 2

-------------------------------------
      |          type1          type2
------+------------------------------
A     |
  fd  | . (0.00) 1.000 . (0.00) 1.000
  ka  | . (0.00) 1.000 . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000
  pr  | . (0.00) 1.000 . (0.00) 1.000
  la  | . (0.00) 1.000 . (0.00) 1.000
B     |
  fd  | . (0.00) 1.000 . (0.00) 1.000
  ka  | . (0.00) 1.000 . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000
  pr  | . (0.00) 1.000 . (0.00) 1.000
  la  | . (0.00) 1.000 . (0.00) 1.000
C     |
  fd  | . (0.00) 1.000 . (0.00) 1.000
  ka  | . (0.00) 1.000 . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000
  pr  | . (0.00) 1.000 . (0.00) 1.000
  la  | . (0.00) 1.000 . (0.00) 1.000
D     |
  fd  | . (0.00) 1.000 . (0.00) 1.000
  ka  | . (0.00) 1.000 . (0.00) 1.000
  ext | . (0.00) 1.000 . (0.00) 1.000
  dom | . (0.00) 1.000 . (0.00) 1.000
  pr  | . (0.00) 1.000 . (0.00) 1.000
  la  | . (0.00) 1.000 . (0.00) 1.000
-------------------------------------
Correlations, (covariances), and p-values.

. collect export table_type.tex, replace
(collection default exported to file table_type.tex)

.
. collect layout (group#rowname) (colname[indicator1]#result[show])

Collection: default
      Rows: group#rowname
   Columns: colname[indicator1]#result[show]
   Table 1: 28 x 1

---------------------------
      |          indicator1
------+--------------------
A     |
  fd  |   0.06 (0.08) 0.798
  ka  | -0.30 (-1.69) 0.150
  ext | -0.76 (-0.72) 0.000
  dom | -0.12 (-0.08) 0.578
  pr  | -0.35 (-1.01) 0.096
  la  |   0.65 (0.79) 0.001
B     |
  fd  | -0.37 (-0.06) 0.198
  ka  | -0.46 (-0.24) 0.096
  ext | -0.44 (-0.02) 0.114
  dom | -0.35 (-0.04) 0.222
  pr  | -0.15 (-0.07) 0.621
  la  | -0.30 (-0.01) 0.296
C     |
  fd  | -0.23 (-0.23) 0.525
  ka  |      . (0.00) 1.000
  ext |      . (0.00) 1.000
  dom | -0.40 (-0.27) 0.254
  pr  | -0.27 (-0.64) 0.451
  la  | -0.42 (-0.03) 0.228
D     |
  fd  | -0.62 (-0.31) 0.001
  ka  |      . (0.00) 1.000
  ext |      . (0.00) 1.000
  dom | -0.37 (-0.07) 0.077
  pr  | -0.16 (-0.11) 0.467
  la  | -0.34 (-0.11) 0.107
---------------------------
Correlations, (covariances), and p-values.

. collect export table_ind.tex, replace
(collection default exported to file table_ind.tex)

.
. collect layout (group#rowname) (colname[decade1 decade2 decade3]#result[show]
> )

Collection: default
      Rows: group#rowname
   Columns: colname[decade1 decade2 decade3]#result[show]
   Table 1: 28 x 3

-------------------------------------------------------------------
      |             decade1             decade2             decade3
------+------------------------------------------------------------
A     |
  fd  | -0.83 (-0.06) 0.000   0.29 (0.02) 0.175   0.47 (0.04) 0.022
  ka  |   0.19 (0.05) 0.386 -0.15 (-0.05) 0.490 -0.02 (-0.00) 0.943
  ext | -0.37 (-0.02) 0.073 -0.04 (-0.00) 0.846   0.39 (0.02) 0.063
  dom | -0.76 (-0.02) 0.000   0.52 (0.02) 0.009   0.16 (0.01) 0.456
  pr  | -0.91 (-0.13) 0.000   0.10 (0.02) 0.648   0.73 (0.12) 0.000
  la  |   0.26 (0.02) 0.214 -0.15 (-0.01) 0.485 -0.09 (-0.01) 0.692
B     |
  fd  | -0.82 (-0.06) 0.000   0.52 (0.04) 0.058   0.32 (0.02) 0.261
  ka  | -0.43 (-0.10) 0.127   0.24 (0.05) 0.413   0.20 (0.04) 0.490
  ext | -0.37 (-0.01) 0.190   0.21 (0.00) 0.478   0.18 (0.00) 0.549
  dom | -0.67 (-0.04) 0.008   0.20 (0.01) 0.497   0.50 (0.03) 0.066
  pr  | -0.98 (-0.20) 0.000   0.38 (0.08) 0.185   0.64 (0.12) 0.014
  la  | -0.70 (-0.01) 0.005 -0.04 (-0.00) 0.881   0.79 (0.01) 0.001
C     |
  fd  | -0.99 (-0.03) 0.000   0.23 (0.01) 0.524   0.37 (0.02) 0.291
  ka  |      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  ext |      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  dom | -0.85 (-0.02) 0.002 -0.16 (-0.01) 0.659   0.69 (0.03) 0.028
  pr  | -0.97 (-0.08) 0.000   0.12 (0.02) 0.745   0.47 (0.06) 0.166
  la  | -0.29 (-0.00) 0.414 -0.13 (-0.00) 0.721   0.31 (0.00) 0.382
D     |
  fd  | -0.96 (-0.05) 0.000   0.44 (0.02) 0.030   0.42 (0.02) 0.040
  ka  |      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  ext |      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  dom | -0.73 (-0.01) 0.000   0.60 (0.01) 0.002   0.04 (0.00) 0.858
  pr  | -0.65 (-0.04) 0.001   0.16 (0.01) 0.467   0.43 (0.03) 0.035
  la  | -0.09 (-0.00) 0.687   0.03 (0.00) 0.899   0.05 (0.00) 0.813
-------------------------------------------------------------------
Correlations, (covariances), and p-values.

. collect export table_decade.tex, replace
(collection default exported to file table_decade.tex)

[Giorgio Di Stefano]

If you have Stata 17 or newer, you can use the collect with
cpcorr to build your table for LaTeX. One challenge here is that
cpcorr does not apply the same row and column names of
r(C) to r(p), so I had to write a short (byable)
wrap-around program to accomplish this. Also the example data does not
have labels on the variables, but if it did, then those labels would
show up in the table instead of the variable names.

Here is the code I used.

program mod_cpcorr, rclass byable(recall)
syntax anything [if] [in] [, *]
marksample touse
cpcorr `anything' if `touse', `options'
tempname C p
matrix `C' = r(C)
matrix `p' = r(p)
matrix colname `p' = `:colfullname `C', quote'
matrix rowname `p' = `:rowfullname `C', quote'
return scalar N = r(N)
return matrix C = `C'
return matrix p = `p'
end

sort group

by group : ///
collect corr=(r(C)) pvalue=(r(p)) : ///
mod_cpcorr fd ka ext dom pr la \ ///
type1 type2 indicator1 decade1 decade2 decade3
by group : ///
collect cov=(r(C)) : ///
mod_cpcorr fd ka ext dom pr la \ ///
type1 type2 indicator1 decade1 decade2 decade3, covariance

* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[pvalue] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov pvalue, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (group#rowname) (colname#result[show])

collect export table.tex, replace

Here is the table.

. collect layout (group#rowname) (colname#result[show])

Collection: default
Rows: group#rowname
Columns: colname#result[show]
Table 1: 28 x 6

---------------------------------------------------------------------------------------------------------------------
| type1 type2 indicator1 decade1 decade2 decade3
------+--------------------------------------------------------------------------------------------------------------
A |
fd | . (0.00) 1.000 . (0.00) 1.000 0.06 (0.08) 0.798 -0.83 (-0.06) 0.000 0.29 (0.02) 0.175 0.47 (0.04) 0.022
ka | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-1.69) 0.150 0.19 (0.05) 0.386 -0.15 (-0.05) 0.490 -0.02 (-0.00) 0.943
ext | . (0.00) 1.000 . (0.00) 1.000 -0.76 (-0.72) 0.000 -0.37 (-0.02) 0.073 -0.04 (-0.00) 0.846 0.39 (0.02) 0.063
dom | . (0.00) 1.000 . (0.00) 1.000 -0.12 (-0.08) 0.578 -0.76 (-0.02) 0.000 0.52 (0.02) 0.009 0.16 (0.01) 0.456
pr | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-1.01) 0.096 -0.91 (-0.13) 0.000 0.10 (0.02) 0.648 0.73 (0.12) 0.000
la | . (0.00) 1.000 . (0.00) 1.000 0.65 (0.79) 0.001 0.26 (0.02) 0.214 -0.15 (-0.01) 0.485 -0.09 (-0.01) 0.692
B |
fd | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.06) 0.198 -0.82 (-0.06) 0.000 0.52 (0.04) 0.058 0.32 (0.02) 0.261
ka | . (0.00) 1.000 . (0.00) 1.000 -0.46 (-0.24) 0.096 -0.43 (-0.10) 0.127 0.24 (0.05) 0.413 0.20 (0.04) 0.490
ext | . (0.00) 1.000 . (0.00) 1.000 -0.44 (-0.02) 0.114 -0.37 (-0.01) 0.190 0.21 (0.00) 0.478 0.18 (0.00) 0.549
dom | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-0.04) 0.222 -0.67 (-0.04) 0.008 0.20 (0.01) 0.497 0.50 (0.03) 0.066
pr | . (0.00) 1.000 . (0.00) 1.000 -0.15 (-0.07) 0.621 -0.98 (-0.20) 0.000 0.38 (0.08) 0.185 0.64 (0.12) 0.014
la | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-0.01) 0.296 -0.70 (-0.01) 0.005 -0.04 (-0.00) 0.881 0.79 (0.01) 0.001
C |
fd | . (0.00) 1.000 . (0.00) 1.000 -0.23 (-0.23) 0.525 -0.99 (-0.03) 0.000 0.23 (0.01) 0.524 0.37 (0.02) 0.291
ka | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000 -0.40 (-0.27) 0.254 -0.85 (-0.02) 0.002 -0.16 (-0.01) 0.659 0.69 (0.03) 0.028
pr | . (0.00) 1.000 . (0.00) 1.000 -0.27 (-0.64) 0.451 -0.97 (-0.08) 0.000 0.12 (0.02) 0.745 0.47 (0.06) 0.166
la | . (0.00) 1.000 . (0.00) 1.000 -0.42 (-0.03) 0.228 -0.29 (-0.00) 0.414 -0.13 (-0.00) 0.721 0.31 (0.00) 0.382
D |
fd | . (0.00) 1.000 . (0.00) 1.000 -0.62 (-0.31) 0.001 -0.96 (-0.05) 0.000 0.44 (0.02) 0.030 0.42 (0.02) 0.040
ka | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.07) 0.077 -0.73 (-0.01) 0.000 0.60 (0.01) 0.002 0.04 (0.00) 0.858
pr | . (0.00) 1.000 . (0.00) 1.000 -0.16 (-0.11) 0.467 -0.65 (-0.04) 0.001 0.16 (0.01) 0.467 0.43 (0.03) 0.035
la | . (0.00) 1.000 . (0.00) 1.000 -0.34 (-0.11) 0.107 -0.09 (-0.00) 0.687 0.03 (0.00) 0.899 0.05 (0.00) 0.813
---------------------------------------------------------------------------------------------------------------------
Correlations, (covariances), and p-values.

This table is rather wide, but you can use collect layout to select
columns and export them separately. For example

. collect layout (group#rowname) (colname[type1 type2]#result[show])

Collection: default
Rows: group#rowname
Columns: colname[type1 type2]#result[show]
Table 1: 28 x 2

-------------------------------------
| type1 type2
------+------------------------------
A |
fd | . (0.00) 1.000 . (0.00) 1.000
ka | . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000
pr | . (0.00) 1.000 . (0.00) 1.000
la | . (0.00) 1.000 . (0.00) 1.000
B |
fd | . (0.00) 1.000 . (0.00) 1.000
ka | . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000
pr | . (0.00) 1.000 . (0.00) 1.000
la | . (0.00) 1.000 . (0.00) 1.000
C |
fd | . (0.00) 1.000 . (0.00) 1.000
ka | . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000
pr | . (0.00) 1.000 . (0.00) 1.000
la | . (0.00) 1.000 . (0.00) 1.000
D |
fd | . (0.00) 1.000 . (0.00) 1.000
ka | . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000
dom | . (0.00) 1.000 . (0.00) 1.000
pr | . (0.00) 1.000 . (0.00) 1.000
la | . (0.00) 1.000 . (0.00) 1.000
-------------------------------------
Correlations, (covariances), and p-values.

. collect export table_type.tex, replace
(collection default exported to file table_type.tex)

.
. collect layout (group#rowname) (colname[indicator1]#result[show])

Collection: default
Rows: group#rowname
Columns: colname[indicator1]#result[show]
Table 1: 28 x 1

---------------------------
| indicator1
------+--------------------
A |
fd | 0.06 (0.08) 0.798
ka | -0.30 (-1.69) 0.150
ext | -0.76 (-0.72) 0.000
dom | -0.12 (-0.08) 0.578
pr | -0.35 (-1.01) 0.096
la | 0.65 (0.79) 0.001
B |
fd | -0.37 (-0.06) 0.198
ka | -0.46 (-0.24) 0.096
ext | -0.44 (-0.02) 0.114
dom | -0.35 (-0.04) 0.222
pr | -0.15 (-0.07) 0.621
la | -0.30 (-0.01) 0.296
C |
fd | -0.23 (-0.23) 0.525
ka | . (0.00) 1.000
ext | . (0.00) 1.000
dom | -0.40 (-0.27) 0.254
pr | -0.27 (-0.64) 0.451
la | -0.42 (-0.03) 0.228
D |
fd | -0.62 (-0.31) 0.001
ka | . (0.00) 1.000
ext | . (0.00) 1.000
dom | -0.37 (-0.07) 0.077
pr | -0.16 (-0.11) 0.467
la | -0.34 (-0.11) 0.107
---------------------------
Correlations, (covariances), and p-values.

. collect export table_ind.tex, replace
(collection default exported to file table_ind.tex)

.
. collect layout (group#rowname) (colname[decade1 decade2 decade3]#result[show]
> )

Collection: default
Rows: group#rowname
Columns: colname[decade1 decade2 decade3]#result[show]
Table 1: 28 x 3

-------------------------------------------------------------------
| decade1 decade2 decade3
------+------------------------------------------------------------
A |
fd | -0.83 (-0.06) 0.000 0.29 (0.02) 0.175 0.47 (0.04) 0.022
ka | 0.19 (0.05) 0.386 -0.15 (-0.05) 0.490 -0.02 (-0.00) 0.943
ext | -0.37 (-0.02) 0.073 -0.04 (-0.00) 0.846 0.39 (0.02) 0.063
dom | -0.76 (-0.02) 0.000 0.52 (0.02) 0.009 0.16 (0.01) 0.456
pr | -0.91 (-0.13) 0.000 0.10 (0.02) 0.648 0.73 (0.12) 0.000
la | 0.26 (0.02) 0.214 -0.15 (-0.01) 0.485 -0.09 (-0.01) 0.692
B |
fd | -0.82 (-0.06) 0.000 0.52 (0.04) 0.058 0.32 (0.02) 0.261
ka | -0.43 (-0.10) 0.127 0.24 (0.05) 0.413 0.20 (0.04) 0.490
ext | -0.37 (-0.01) 0.190 0.21 (0.00) 0.478 0.18 (0.00) 0.549
dom | -0.67 (-0.04) 0.008 0.20 (0.01) 0.497 0.50 (0.03) 0.066
pr | -0.98 (-0.20) 0.000 0.38 (0.08) 0.185 0.64 (0.12) 0.014
la | -0.70 (-0.01) 0.005 -0.04 (-0.00) 0.881 0.79 (0.01) 0.001
C |
fd | -0.99 (-0.03) 0.000 0.23 (0.01) 0.524 0.37 (0.02) 0.291
ka | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
dom | -0.85 (-0.02) 0.002 -0.16 (-0.01) 0.659 0.69 (0.03) 0.028
pr | -0.97 (-0.08) 0.000 0.12 (0.02) 0.745 0.47 (0.06) 0.166
la | -0.29 (-0.00) 0.414 -0.13 (-0.00) 0.721 0.31 (0.00) 0.382
D |
fd | -0.96 (-0.05) 0.000 0.44 (0.02) 0.030 0.42 (0.02) 0.040
ka | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
ext | . (0.00) 1.000 . (0.00) 1.000 . (0.00) 1.000
dom | -0.73 (-0.01) 0.000 0.60 (0.01) 0.002 0.04 (0.00) 0.858
pr | -0.65 (-0.04) 0.001 0.16 (0.01) 0.467 0.43 (0.03) 0.035
la | -0.09 (-0.00) 0.687 0.03 (0.00) 0.899 0.05 (0.00) 0.813
-------------------------------------------------------------------
Correlations, (covariances), and p-values.

. collect export table_decade.tex, replace
(collection default exported to file table_decade.tex)

Thank you warmly for your work , Jeff! I really appreciate it!
That was beyond my abilities!
I have some questions about the code, rather silly ones.

Assume that I would like to rename each of the groups A, B, C, D, E, etc. to another group name, say "Whatever A" and "Whatever B," etc. How could I do that?


Secondly, on my dataset, the variables are already labeled. I would like to have them placed vertically on the table rather than horizontally.

Finally, for a new similar table, I would like to have the group description (A, B, etc.) the same way they are for both the rows and the column ("Whatever in column A," etc.).

Thank you so much! .

[Giorgio Di Stefano]

To provide clarity, let me say that in the rows for the data example here, group A is composed of fd and ka.

Group B is composed of ext and dom.

Group C is composed of pr and la.

In the real data, I have five groups and more variables in each group.

[Jeff Pitblado (StataCorp)]

I assumed string variable group in your example dataset defined
the groups A, B, C, .... Let me start over again.

I made a new program named both_cpcorr that calls cpcorr
to get correlations, covariances, and p-values in one call (and still
copies the matrix stripes from the correlations matrix to the p-values
matrix).

In this example I collect results for the given variable groups
A (fd ka), B (ext dom), and C (pr la), separately and provide a custom tag for
each group using a dimension I name var_group with levels A,
B, and C. Next I show how to attach your own labels to these
levels, apply the same cell and header styles at the previous example, and
finally change the layout to put all variables in the row specification,
nesting the reported column variables within the row variables which are
nested within the variables group dimension var_group.

program both_cpcorr, rclass byable(recall)
    // use -cpcorr- to post both CORRelations and COVariances;
    // ensure posted p-values matrix has the same matrix stripes as
    // the corr/cov matrices
    version 17
    syntax anything [if] [in]
    marksample touse
    cpcorr `anything' if `touse'
    tempname C p
    matrix `C' = r(C)
    matrix `p' = r(p)
    matrix colname `p' = `:colfullname `C', quote'
    matrix rowname `p' = `:rowfullname `C', quote'
    return scalar N = r(N)
    return matrix corr = `C'
    return matrix p = `p'
    cpcorr `anything' if `touse', covariance
    matrix `C' = r(C)
    return matrix cov = `C'
end

local common type1 type2 indicator1 decade1 decade2 decade3

* Group A variables
collect, tags(var_group[A]) : both_cpcorr fd ka \ `common'
* Group B variables
collect, tags(var_group[B]) : both_cpcorr ext dom \ `common'
* Group C variables
collect, tags(var_group[C]) : both_cpcorr pr la \ `common'

* label the var_group levels
collect label levels var_group ///
    A "Whatever A" ///
    B "Whatever B" ///
    C "Whatever C"

* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[p] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov p, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (var_group#rowname#colname) (result[show])

Here is the resulting table.

. collect layout (var_group#rowname#colname) (result[show])

Collection: default
      Rows: var_group#rowname#colname
   Columns: result[show]
   Table 1: 45 x 1

------------------------------------
Whatever A     |
  fd           |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 | -0.04 (-0.04) 0.727
    decade1    | -0.80 (-0.05) 0.000
    decade2    |   0.34 (0.02) 0.003
    decade3    |   0.38 (0.03) 0.001
  ka           |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 | -0.29 (-0.97) 0.012
    decade1    | -0.02 (-0.00) 0.875
    decade2    | -0.02 (-0.00) 0.893
    decade3    |   0.03 (0.01) 0.775
Whatever B     |
  ext          |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 | -0.58 (-0.34) 0.000
    decade1    | -0.19 (-0.01) 0.105
    decade2    | -0.00 (-0.00) 1.000
    decade3    |   0.18 (0.01) 0.137
  dom          |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 | -0.01 (-0.01) 0.910
    decade1    | -0.62 (-0.02) 0.000
    decade2    |   0.29 (0.01) 0.013
    decade3    |   0.26 (0.01) 0.026
Whatever C     |
  pr           |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 | -0.25 (-0.54) 0.034
    decade1    | -0.79 (-0.11) 0.000
    decade2    |   0.18 (0.03) 0.140
    decade3    |   0.54 (0.08) 0.000
  la           |
    type1      |      . (0.00) 1.000
    type2      |      . (0.00) 1.000
    indicator1 |   0.29 (0.30) 0.013
    decade1    |   0.06 (0.00) 0.639
    decade2    | -0.05 (-0.00) 0.697
    decade3    | -0.00 (-0.00) 0.981
------------------------------------
Correlations, (covariances), and p-values.

[Jeff Pitblado (StataCorp)]

Here is a modified version of the previous where you do want the
correlations within the levels of the group variable.

collect create within_group, replace
sort group
local common type1 type2 indicator1 decade1 decade2 decade3

* Group A variables
by group: collect, tags(var_group[A]) : both_cpcorr fd ka \ `common'
* Group B variables
by group: collect, tags(var_group[B]) : both_cpcorr ext dom \ `common'
* Group C variables
by group: collect, tags(var_group[C]) : both_cpcorr pr la \ `common'

* label the var_group levels
collect label levels var_group ///
    A "Whatever A" ///
    B "Whatever B" ///
    C "Whatever C"

collect levels group
local levels = s(levels)
foreach lev of local levels {
    collect label levels group `lev' "Sample `lev'"
}

* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[p] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov p, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (group#var_group#rowname#colname) (result[show])

Here is the resulting table.

. collect layout (group#var_group#rowname#colname) (result[show])

Collection: within_group
      Rows: group#var_group#rowname#colname
   Columns: result[show]
   Table 1: 184 x 1

--------------------------------------
Sample A         |
  Whatever A     |
    fd           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |   0.06 (0.08) 0.798
      decade1    | -0.83 (-0.06) 0.000
      decade2    |   0.29 (0.02) 0.175
      decade3    |   0.47 (0.04) 0.022
    ka           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.30 (-1.69) 0.150
      decade1    |   0.19 (0.05) 0.386
      decade2    | -0.15 (-0.05) 0.490
      decade3    | -0.02 (-0.00) 0.943
  Whatever B     |
    ext          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.76 (-0.72) 0.000
      decade1    | -0.37 (-0.02) 0.073
      decade2    | -0.04 (-0.00) 0.846
      decade3    |   0.39 (0.02) 0.063
    dom          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.12 (-0.08) 0.578
      decade1    | -0.76 (-0.02) 0.000
      decade2    |   0.52 (0.02) 0.009
      decade3    |   0.16 (0.01) 0.456
  Whatever C     |
    pr           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.35 (-1.01) 0.096
      decade1    | -0.91 (-0.13) 0.000
      decade2    |   0.10 (0.02) 0.648
      decade3    |   0.73 (0.12) 0.000
    la           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |   0.65 (0.79) 0.001
      decade1    |   0.26 (0.02) 0.214
      decade2    | -0.15 (-0.01) 0.485
      decade3    | -0.09 (-0.01) 0.692
Sample B         |
  Whatever A     |
    fd           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.37 (-0.06) 0.198
      decade1    | -0.82 (-0.06) 0.000
      decade2    |   0.52 (0.04) 0.058
      decade3    |   0.32 (0.02) 0.261
    ka           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.46 (-0.24) 0.096
      decade1    | -0.43 (-0.10) 0.127
      decade2    |   0.24 (0.05) 0.413
      decade3    |   0.20 (0.04) 0.490
  Whatever B     |
    ext          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.44 (-0.02) 0.114
      decade1    | -0.37 (-0.01) 0.190
      decade2    |   0.21 (0.00) 0.478
      decade3    |   0.18 (0.00) 0.549
    dom          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.35 (-0.04) 0.222
      decade1    | -0.67 (-0.04) 0.008
      decade2    |   0.20 (0.01) 0.497
      decade3    |   0.50 (0.03) 0.066
  Whatever C     |
    pr           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.15 (-0.07) 0.621
      decade1    | -0.98 (-0.20) 0.000
      decade2    |   0.38 (0.08) 0.185
      decade3    |   0.64 (0.12) 0.014
    la           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.30 (-0.01) 0.296
      decade1    | -0.70 (-0.01) 0.005
      decade2    | -0.04 (-0.00) 0.881
      decade3    |   0.79 (0.01) 0.001
Sample C         |
  Whatever A     |
    fd           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.23 (-0.23) 0.525
      decade1    | -0.99 (-0.03) 0.000
      decade2    |   0.23 (0.01) 0.524
      decade3    |   0.37 (0.02) 0.291
    ka           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |      . (0.00) 1.000
      decade1    |      . (0.00) 1.000
      decade2    |      . (0.00) 1.000
      decade3    |      . (0.00) 1.000
  Whatever B     |
    ext          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |      . (0.00) 1.000
      decade1    |      . (0.00) 1.000
      decade2    |      . (0.00) 1.000
      decade3    |      . (0.00) 1.000
    dom          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.40 (-0.27) 0.254
      decade1    | -0.85 (-0.02) 0.002
      decade2    | -0.16 (-0.01) 0.659
      decade3    |   0.69 (0.03) 0.028
  Whatever C     |
    pr           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.27 (-0.64) 0.451
      decade1    | -0.97 (-0.08) 0.000
      decade2    |   0.12 (0.02) 0.745
      decade3    |   0.47 (0.06) 0.166
    la           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.42 (-0.03) 0.228
      decade1    | -0.29 (-0.00) 0.414
      decade2    | -0.13 (-0.00) 0.721
      decade3    |   0.31 (0.00) 0.382
Sample D         |
  Whatever A     |
    fd           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.62 (-0.31) 0.001
      decade1    | -0.96 (-0.05) 0.000
      decade2    |   0.44 (0.02) 0.030
      decade3    |   0.42 (0.02) 0.040
    ka           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |      . (0.00) 1.000
      decade1    |      . (0.00) 1.000
      decade2    |      . (0.00) 1.000
      decade3    |      . (0.00) 1.000
  Whatever B     |
    ext          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 |      . (0.00) 1.000
      decade1    |      . (0.00) 1.000
      decade2    |      . (0.00) 1.000
      decade3    |      . (0.00) 1.000
    dom          |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.37 (-0.07) 0.077
      decade1    | -0.73 (-0.01) 0.000
      decade2    |   0.60 (0.01) 0.002
      decade3    |   0.04 (0.00) 0.858
  Whatever C     |
    pr           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.16 (-0.11) 0.467
      decade1    | -0.65 (-0.04) 0.001
      decade2    |   0.16 (0.01) 0.467
      decade3    |   0.43 (0.03) 0.035
    la           |
      type1      |      . (0.00) 1.000
      type2      |      . (0.00) 1.000
      indicator1 | -0.34 (-0.11) 0.107
      decade1    | -0.09 (-0.00) 0.687
      decade2    |   0.03 (0.00) 0.899
      decade3    |   0.05 (0.00) 0.813
--------------------------------------
Correlations, (covariances), and p-values.

[Jeff Pitblado (StataCorp)]

If neither of these examples matches what you want, please provide example tables.

[Giorgio Di Stefano]

If neither of these examples matches what you want, please provide example tables.

Table in #5 is the desired wide form. However, with two modifications, I would like to be able to label A, B, C, D, E, etc. as in #8.

* Label the var_group levels

collect label levels var_group ///

A "Whatever A"

B "Whatever B" ///

 C "Whatever C"

In addition to being able to add the wanted variables to each group in A, B, C etc.



Say for “Whatever A" fd and ka, for "Whatever B " ext and dom, and for “Whatever C” pr and la. and so on . The rest looks fine!

[Giorgio Di Stefano]

Jeff Pitblado (StataCorp) I
I got

 collect layout (group#rowname) (colname#result[show]),name(within_group)

Collection: within_group
      Rows: group#rowname
   Columns: colname#result[show]

Your layout specification does not uniquely match any items. One or more of the following dimensions
might help uniquely match items: cmdset, rowname, var_group.

.
The full code I run is :

program both_cpcorr, rclass byable(recall)
    // use -cpcorr- to post both CORRelations and COVariances;
    // ensure posted p-values matrix has the same matrix stripes as
    // the corr/cov matrices
    version 17
    syntax anything [if] [in]
    marksample touse
    cpcorr `anything' if `touse'
    tempname C p
    matrix `C' = r(C)
    matrix `p' = r(p)
    matrix colname `p' = `:colfullname `C', quote'
    matrix rowname `p' = `:rowfullname `C', quote'
    return scalar N = r(N)
    return matrix corr = `C'
    return matrix p = `p'
    cpcorr `anything' if `touse', covariance
    matrix `C' = r(C)
    return matrix cov = `C'
end


collect create within_group, replace
sort group
local common type1 type2 indicator1 decade1 decade2 decade3

* Group A variables
by group: collect, tags(var_group[A]) : both_cpcorr fd ka \ `common'
* Group B variables
by group: collect, tags(var_group[B]) : both_cpcorr ext dom \ `common'
* Group C variables
by group: collect, tags(var_group[C]) : both_cpcorr pr la \ `common'

* label the var_group levels
collect label levels var_group ///
    A "Whatever A" ///
    B "Whatever B" ///
    C "Whatever C"
    
    
    
* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[p] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov p, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (group#var_group#rowname#colname) (result[show])

Any suggestion ?

[Jeff Pitblado (StataCorp)]

It appears you are missing var_group.

collect layout (group#var_group#rowname) (colname#result[show]), name(within_group)

[Giorgio Di Stefano]

It appears you are missing var_group.

collect layout (group#var_group#rowname) (colname#result[show]), name(within_group)

I still get

Your layout specification does not uniquely match any items. One or more of the following dimensions
might help uniquely match items: cmdset, rowname, var_group.

My desired layout is

Var1. Var2 Var3 Var4 etc a columns

Group A name
GROUP_A_Var 1
GROUP_A_Var 2

Group B name
GROUP_B_Var 1
GROUP_B_Var 2
GROUP_B_Var 3

Group C name
GROUP_C_Var 1
GROUP_C_Var 2
GROUP_C_Var 3
GROUP_C_Var 4

etc Enable GingerCannot connect to Ginger Check your internet connection
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[Jeff Pitblado (StataCorp)]

Maybe start with a fresh Stata session, or type clear all before rerunning your code.

This is the code I ran.

clear all

* Example generated by -dataex-. For more info, type help dataex
clear
input float(id year) str97 country str1 group float(fd ka ext dom pr la type1 type2 indicator1 decade) byte(decade1 decade2 decade3)
1 1992 "Country1" "A"   .524175   2.321955  .75 .7777778 .071428575        1 0 1       12.2 1990 1 0 0
1 1993 "Country1" "A"  .5846328   2.321955  .75 .7777778 .071428575        1 0 1  17.553352 1990 1 0 0
1 1994 "Country1" "A"  .6478685   2.321955  .75 .9444444 .071428575 .7912164 0 1      19.11 1990 1 0 0
1 2000 "Country1" "A"  .8414965   1.048859  .75        1  .53571427 .7782844 0 1     28.634 2000 0 1 0
1 2001 "Country1" "A"   .873997   1.048859  .75        1   .6190476 .7782844 0 1   26.41307 2000 0 1 0
1 2002 "Country1" "A"  .8985876   1.048859  .75        1   .6190476 .7661784 0 1   5.536341 2000 0 1 0
1 2003 "Country1" "A"  .9015374   1.048859  .75        1   .6190476 .7661784 0 1   5.536341 2000 0 1 0
1 2004 "Country1" "A"  .9041975   1.048859  .75        1   .6190476 .7661784 0 1   7.350179 2000 0 1 0
1 2010 "Country1" "A"   .941813   1.048859 .875        1   .8452381 .7704133 0 1   6.241802 2010 0 0 1
1 2011 "Country1" "A"   .934702   1.048859 .875        1   .8452381 .7704133 0 1      5.068 2010 0 0 1
1 2012 "Country1" "A"  .9079577   1.303478 .875        1   .8452381 .7704133 0 1      5.068 2010 0 0 1
1 2013 "Country1" "A"  .8901507  1.5580974 .875        1   .8452381 .7694158 0 1   7.929047 2010 0 0 1
2 1992 "Country2" "A"   .399736   .6099069 .875 .7777778          0 .5697657 0 1        1.6 1990 1 0 0
2 1993 "Country2" "A"   .461959  2.0673358 .875 .9444444          0 .5697657 0 1   6.996447 1990 1 0 0
2 1994 "Country2" "A"  .4953545   2.321955 .875 .9444444          0 .5697657 0 1    8.69136 1990 1 0 0
2 2000 "Country2" "A"  .7018992   2.321955    1        1   .4404762 .5697657 0 1   2.364474 2000 0 1 0
2 2001 "Country2" "A"  .7035186   2.321955    1        1   .5952381 .5697657 0 1   2.364474 2000 0 1 0
2 2002 "Country2" "A"  .6993845   2.321955    1        1   .5952381 .5457992 0 1  -.7668521 2000 0 1 0
2 2003 "Country2" "A"  .7077955   2.321955    1        1   .5952381 .5457992 0 1 -2.9592714 2000 0 1 0
2 2004 "Country2" "A"   .728983   2.321955    1        1   .5952381 .5457992 0 1  -2.950783 2000 0 1 0
2 2010 "Country2" "A"  .7894757   2.321955    1 .9444444   .9166667 .5718316 0 1      3.891 2010 0 0 1
2 2011 "Country2" "A"  .8007692   2.321955    1 .9444444   .9166667 .5718316 0 1      3.891 2010 0 0 1
2 2012 "Country2" "A"  .7593077   2.321955    1 .9444444   .9166667 .5718316 0 1 -2.5410414 2010 0 0 1
2 2013 "Country2" "A"  .7435991   2.321955    1 .9444444   .9166667 .5718316 0 1  -6.333579 2010 0 0 1
3 1992 "Country3" "B"  .5840359   2.321955    1 .7777778  .08333334 .6281998 0 1   .3835026 1990 1 0 0
3 1993 "Country3" "B"  .6147648   2.321955    1 .8888889  .08333334 .6281998 0 1   .3835026 1990 1 0 0
3 1994 "Country3" "B"   .632942   2.321955    1 .8888889  .08333334 .6260909 0 1   .8169867 1990 1 0 0
3 2000 "Country3" "B"  .7692201   2.321955    1 .8888889        .75 .6297867 0 1  1.9049623 2000 0 1 0
3 2001 "Country3" "B"  .7502941   2.321955    1 .8888889        .75 .6297867 0 1  1.9049622 2000 0 1 0
3 2002 "Country3" "B"  .7244223   2.321955    1 .8888889   .8333333 .6297867 0 1   1.283737 2000 0 1 0
3 2003 "Country3" "B"  .7401305   2.321955    1 .8888889   .8333333 .6297867 0 1 -1.3254085 2000 0 1 0
3 2004 "Country3" "B"  .7518873   2.321955    1 .8888889   .8333333 .6547069 0 1 -1.3254085 2000 0 1 0
3 2010 "Country3" "B"  .7356597   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2011 "Country3" "B"  .7201834   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2012 "Country3" "B"  .7283527   2.321955    1 .9444444          1 .6547069 0 1  1.1606808 2010 0 0 1
3 2013 "Country3" "B"  .7077386   2.321955    1 .9444444          1 .6547069 0 1  1.1165322 2010 0 0 1
4 1992 "Country4" "B"  .3452282   .6099069 .875 .5555556 .071428575 .6121462 0 1   2.615249 1990 1 0 0
4 1993 "Country4" "B"  .3790323  2.0673358    1 .7222222 .071428575 .6121462 0 1  1.4437795 1990 1 0 0
4 1994 "Country5" "C"  .4175321   2.321955    1 .7222222 .071428575 .6121462 0 1  4.0116615 1990 1 0 0
4 2000 "Country5" "C"   .759881   2.321955    1 .8888889   .7619048 .6121462 0 1    5.97681 2000 0 1 0
4 2001 "Country5" "C"  .7410694   2.321955    1 .8888889   .7619048 .6121462 0 1   7.402936 2000 0 1 0
4 2002 "Country5" "C"  .7281089   2.321955    1 .8888889   .8333333 .6121462 0 1      8.534 2000 0 1 0
4 2003 "Country5" "C"   .735869   2.321955    1 .8888889   .8333333 .6263371 0 1      8.534 2000 0 1 0
4 2004 "Country5" "C"  .7334849   2.321955    1 .8888889   .8333333 .6263371 0 1      8.534 2000 0 1 0
4 2010 "Country5" "C"  .7798166   2.321955    1 .9444444   .9166667 .6263371 0 1     -16.25 2010 0 0 1
4 2011 "Country5" "C"  .7637033   2.321955    1 .9444444   .9166667 .6263371 0 1 -14.330358 2010 0 0 1
4 2012 "Country5" "C"  .7608096   2.321955    1 .9444444   .9166667 .6263371 0 1          0 2010 0 0 1
4 2013 "Country5" "C"  .7455279   2.321955    1        1   .9166667  .607849 0 1   .6806767 2010 0 0 1
5 1992 "Country6" "C"  .1757301          .    .        .          .        . 0 1          . 1990 1 0 0
5 1993 "Country6" "C"  .1761862          .    .        .          .        . 1 0          . 1990 1 0 0
5 1994 "Country6" "C"  .1562944          .    .        .          .        . 1 0          . 1990 1 0 0
5 2000 "Country6" "C"  .2008834 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2001 "Country6" "C" .17261477 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2002 "Country6" "C" .21249928 -1.2261546    .        .          .        . 1 0          . 2000 0 1 0
5 2003 "Country6" "C"  .2206576 -.02334493    .        .          .        . 1 0          . 2000 0 1 0
5 2004 "Country6" "C" .23541167 -.02334493    .        .          .        . 1 0          . 2000 0 1 0
5 2010 "Country6" "C" .27683625   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2011 "Country6" "C" .27487376   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2012 "Country6" "C" .27767062   1.249751    .        .          .        . 0 1          . 2010 0 0 1
5 2013 "Country6" "C"  .2884341   1.249751    .        .          .        . 0 1          . 2010 0 0 1
6 1992 "Country7" "C" .25534174  -.1539507 .625       .5          0 .8271327 1 0          . 1990 1 0 0
6 1993 "Country7" "C" .28078705  -.1539507 .625       .5  .16666667 .8271327 1 0          . 1990 1 0 0
6 1994 "Country7" "C"  .3567602  -.1539507 .625 .5555556  .16666667 .8271327 1 0          . 1990 1 0 0
6 2000 "Country7" "C"  .4190661 -1.2261546 .625 .6111111  .23809524 .8271327 0 1          . 2000 0 1 0
6 2001 "Country7" "C"  .3738855 -1.2261546 .625 .6666667   .3928571 .8271327 0 1          . 2000 0 1 0
6 2002 "Country7" "C"   .404098 -1.2261546 .625 .6666667   .3928571 .8271327 0 1          . 2000 0 1 0
6 2003 "Country7" "C"  .4157713 -1.2261546 .875 .6666667   .3928571 .7653575 0 1          . 2000 0 1 0
6 2004 "Country7" "C"  .4085605 -1.2261546 .875 .6666667  .53571427 .7653575 0 1          . 2000 0 1 0
6 2010 "Country7" "C"  .4888775 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2011 "Country7" "C"  .4789392 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2012 "Country7" "C"  .4922497 -.02334493 .875 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
6 2013 "Country7" "C"   .508882 -.02334493  .75 .6666667   .7619048 .7653575 0 1          . 2010 0 0 1
7 1992 "Country8" "D" .56565696   2.321955    1 .9444444   .7738096 .8009957 0 1  13.403038 1990 1 0 0
7 1993 "Country8" "D"  .6403931   2.321955    1 .9444444   .7738096 .8070084 0 1       12.1 1990 1 0 0
7 1994 "Country8" "D"  .6921942   2.321955    1 .9444444   .8452381 .8070084 0 1       12.1 1990 1 0 0
7 2000 "Country8" "D"  .8552948   2.321955    1        1   .9285714 .8314556 0 1      1.806 2000 0 1 0
7 2001 "Country8" "D"  .8805222   2.321955    1        1   .9285714 .8314556 0 1   1.958802 2000 0 1 0
7 2002 "Country8" "D"  .8265579   2.321955    1        1   .9285714 .8314556 0 1      2.076 2000 0 1 0
7 2003 "Country8" "D"  .8580942   2.321955    1        1          1 .8314556 0 1      2.076 2000 0 1 0
7 2004 "Country8" "D"  .8708485   2.321955    1        1          1 .8314556 0 1      2.076 2000 0 1 0
7 2010 "Country8" "D"  .8683383   2.321955    1        1          1 .8314556 0 1   3.564247 2010 0 0 1
7 2011 "Country8" "D"  .8672714   2.321955    1 .9444444          1 .8314556 0 1   5.454876 2010 0 0 1
7 2012 "Country8" "D"  .8684435   2.321955    1 .8888889          1 .8429364 0 1   5.454876 2010 0 0 1
7 2013 "Country8" "D"  .8866873   2.321955    1 .9444444          1 .8429364 0 1   5.454876 2010 0 0 1
8 1992 "Country8" "D"  .5748482   2.321955    1 .8888889  .52380955 .9702252 0 1       14.9 1990 1 0 0
8 1993 "Country8" "D"  .6702072   2.321955    1 .8888889  .52380955 .9702252 0 1   .0375137 1990 1 0 0
8 1994 "Country8" "D"  .6812267   2.321955    1 .8888889  .52380955 .9702252 0 1      -.781 1990 1 0 0
8 2000 "Country8" "D"  .8790284   2.321955    1        1        .75 .9702252 0 1      1.463 2000 0 1 0
8 2001 "Country8" "D"   .889005   2.321955    1        1        .75 .9702252 0 1   5.542341 2000 0 1 0
8 2002 "Country8" "D"  .8849987   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2003 "Country8" "D"  .8916724   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2004 "Country8" "D"  .8910962   2.321955    1        1        .75 .9702252 0 1      5.767 2000 0 1 0
8 2010 "Country8" "D"  .8951228   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2011 "Country8" "D"  .8785759   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2012 "Country8" "D"  .8894278   2.321955    1        1   .8333333 .9702252 0 1       -.36 2010 0 0 1
8 2013 "Country8" "D"  .8901961   2.321955    1        1   .8333333 .9702252 0 1   1.298654 2010 0 0 1
end

program both_cpcorr, rclass byable(recall)
    // use -cpcorr- to post both CORRelations and COVariances;
    // ensure posted p-values matrix has the same matrix stripes as
    // the corr/cov matrices
    version 17
    syntax anything [if] [in]
    marksample touse
    cpcorr `anything' if `touse'
    tempname C p
    matrix `C' = r(C)
    matrix `p' = r(p)
    matrix colname `p' = `:colfullname `C', quote'
    matrix rowname `p' = `:rowfullname `C', quote'
    return scalar N = r(N)
    return matrix corr = `C'
    return matrix p = `p'
    cpcorr `anything' if `touse', covariance
    matrix `C' = r(C)
    return matrix cov = `C'
end

collect create within_group, replace
sort group
local common type1 type2 indicator1 decade1 decade2 decade3

* Group A variables
by group: collect, tags(var_group[A]) : both_cpcorr fd ka \ `common'
* Group B variables
by group: collect, tags(var_group[B]) : both_cpcorr ext dom \ `common'
* Group C variables
by group: collect, tags(var_group[C]) : both_cpcorr pr la \ `common'

* label the var_group levels
collect label levels var_group ///
    A "Whatever A" ///
    B "Whatever B" ///
    C "Whatever C"

* apply some style choices on the results of interest
collect style cell result[cov], sformat("(%s)")
collect style cell result[corr cov] , nformat(%12.2f)
collect style cell result[p] , nformat(%5.3f)
* define composite result named show
collect composite define show = corr cov p, trim
* hide result names from the header
collect style header result, level(hide)
* add note detailing the cell contents
collect notes "Correlations, (covariances), and p-values."

collect layout (group#var_group#rowname) (colname#result[show])

This is the resulting table.

. collect layout (group#var_group#rowname) (colname#result[show])

Collection: within_group
      Rows: group#var_group#rowname
   Columns: colname#result[show]
   Table 1: 40 x 6

----------------------------------------------------------------------------------------------------------------------------
             |          type1          type2          indicator1             decade1             decade2             decade3
-------------+--------------------------------------------------------------------------------------------------------------
A            |                                                                                                              
  Whatever A |                                                                                                              
    fd       | . (0.00) 1.000 . (0.00) 1.000   0.06 (0.08) 0.798 -0.83 (-0.06) 0.000   0.29 (0.02) 0.175   0.47 (0.04) 0.022
    ka       | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-1.69) 0.150   0.19 (0.05) 0.386 -0.15 (-0.05) 0.490 -0.02 (-0.00) 0.943
  Whatever B |                                                                                                              
    ext      | . (0.00) 1.000 . (0.00) 1.000 -0.76 (-0.72) 0.000 -0.37 (-0.02) 0.073 -0.04 (-0.00) 0.846   0.39 (0.02) 0.063
    dom      | . (0.00) 1.000 . (0.00) 1.000 -0.12 (-0.08) 0.578 -0.76 (-0.02) 0.000   0.52 (0.02) 0.009   0.16 (0.01) 0.456
  Whatever C |                                                                                                              
    pr       | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-1.01) 0.096 -0.91 (-0.13) 0.000   0.10 (0.02) 0.648   0.73 (0.12) 0.000
    la       | . (0.00) 1.000 . (0.00) 1.000   0.65 (0.79) 0.001   0.26 (0.02) 0.214 -0.15 (-0.01) 0.485 -0.09 (-0.01) 0.692
B            |                                                                                                              
  Whatever A |                                                                                                              
    fd       | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.06) 0.198 -0.82 (-0.06) 0.000   0.52 (0.04) 0.058   0.32 (0.02) 0.261
    ka       | . (0.00) 1.000 . (0.00) 1.000 -0.46 (-0.24) 0.096 -0.43 (-0.10) 0.127   0.24 (0.05) 0.413   0.20 (0.04) 0.490
  Whatever B |                                                                                                              
    ext      | . (0.00) 1.000 . (0.00) 1.000 -0.44 (-0.02) 0.114 -0.37 (-0.01) 0.190   0.21 (0.00) 0.478   0.18 (0.00) 0.549
    dom      | . (0.00) 1.000 . (0.00) 1.000 -0.35 (-0.04) 0.222 -0.67 (-0.04) 0.008   0.20 (0.01) 0.497   0.50 (0.03) 0.066
  Whatever C |                                                                                                              
    pr       | . (0.00) 1.000 . (0.00) 1.000 -0.15 (-0.07) 0.621 -0.98 (-0.20) 0.000   0.38 (0.08) 0.185   0.64 (0.12) 0.014
    la       | . (0.00) 1.000 . (0.00) 1.000 -0.30 (-0.01) 0.296 -0.70 (-0.01) 0.005 -0.04 (-0.00) 0.881   0.79 (0.01) 0.001
C            |                                                                                                              
  Whatever A |                                                                                                              
    fd       | . (0.00) 1.000 . (0.00) 1.000 -0.23 (-0.23) 0.525 -0.99 (-0.03) 0.000   0.23 (0.01) 0.524   0.37 (0.02) 0.291
    ka       | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  Whatever B |                                                                                                              
    ext      | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
    dom      | . (0.00) 1.000 . (0.00) 1.000 -0.40 (-0.27) 0.254 -0.85 (-0.02) 0.002 -0.16 (-0.01) 0.659   0.69 (0.03) 0.028
  Whatever C |                                                                                                              
    pr       | . (0.00) 1.000 . (0.00) 1.000 -0.27 (-0.64) 0.451 -0.97 (-0.08) 0.000   0.12 (0.02) 0.745   0.47 (0.06) 0.166
    la       | . (0.00) 1.000 . (0.00) 1.000 -0.42 (-0.03) 0.228 -0.29 (-0.00) 0.414 -0.13 (-0.00) 0.721   0.31 (0.00) 0.382
D            |                                                                                                              
  Whatever A |                                                                                                              
    fd       | . (0.00) 1.000 . (0.00) 1.000 -0.62 (-0.31) 0.001 -0.96 (-0.05) 0.000   0.44 (0.02) 0.030   0.42 (0.02) 0.040
    ka       | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
  Whatever B |                                                                                                              
    ext      | . (0.00) 1.000 . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000      . (0.00) 1.000
    dom      | . (0.00) 1.000 . (0.00) 1.000 -0.37 (-0.07) 0.077 -0.73 (-0.01) 0.000   0.60 (0.01) 0.002   0.04 (0.00) 0.858
  Whatever C |                                                                                                              
    pr       | . (0.00) 1.000 . (0.00) 1.000 -0.16 (-0.11) 0.467 -0.65 (-0.04) 0.001   0.16 (0.01) 0.467   0.43 (0.03) 0.035
    la       | . (0.00) 1.000 . (0.00) 1.000 -0.34 (-0.11) 0.107 -0.09 (-0.00) 0.687   0.03 (0.00) 0.899   0.05 (0.00) 0.813
----------------------------------------------------------------------------------------------------------------------------
Correlations, (covariances), and p-values.