Compute an estimate of the grand mean/intercept and differences from the grand - ----------------------------------------------------------------------------- > -
^grand^ indicator_variable_list [^, l^evel^(^#^)^ ]
Description - -----------
For use after ^fit^ to present a set of indicator/dummy variables in a "grand mean" and difference from the "grand mean" form. The specified list of variables (indicator_variable_list) must be orthogonal and completely span the space. The model estimated by fit must include the complete list of indicator variables that fully span space. Use the ^hascons^ or ^nocons^ on ^fit^ to allow the full set of indicators to be included in the model.
Note, -grand- cannot be used after -regress-, it requires some of the results stored by -fit-.
Options - -------
^level(^#^)^ specifies the confidence level, in percent, for confidence interva > ls; see help @level@.
Example - -------
Using the auto data, generate a full set of mutually exclusive indicators for repair record.
. tab rep78, gen(reprec)
Repair | Record 1978 | Freq. Percent Cum. - ------------+----------------------------------- 1 | 2 2.90 2.90 2 | 8 11.59 14.49 3 | 30 43.48 57.97 4 | 18 26.09 84.06 5 | 11 15.94 100.00 - ------------+----------------------------------- Total | 69 100.00
Estimate the full model using -fit- with the -hascons- option.
. fit price displ reprec*, hascons
Source | SS df MS Number of obs = 69 - ---------+------------------------------ F( 5, 63) = 7.3 > 6 Model | 212659562 5 42531912.4 Prob > F = 0.0000 Residual | 364137397 63 5779958.68 R-squared = 0.3687 - ---------+------------------------------ Adj R-squared = 0.318 > 6 Total | 576796959 68 8482308.22 Root MSE = 2404.2
- ----------------------------------------------------------------------------- > - price | Coef. Std. Err. t P>|t| [95% Conf. Interval] - ---------+------------------------------------------------------------------- > - displ | 21.21876 3.569023 5.945 0.000 14.08664 28.35089 reprec1 | 511.7159 1831.576 0.279 0.781 -3148.397 4171.829 reprec2 | 827.3793 1212.444 0.682 0.497 -1595.497 3250.255 reprec3 | 1548.21 930.9655 1.663 0.101 -312.1759 3408.596 reprec4 | 2276.878 853.5133 2.668 0.010 571.2674 3982.488 reprec5 | 3555.788 826.2275 4.304 0.000 1904.704 5206.872 - ----------------------------------------------------------------------------- > -
Obtain the grand means and "marginal" differences by specifying the full set of orthogonal indicators on the -grand- command line.
. grand reprec*
Estimate of grand mean/intercept and marginal impacts - ----------------------------------------------------------------------------- > - price | Coef. Std. Err. t P>|t| [95% Conf. Interval] - ---------+------------------------------------------------------------------- > - grand | 1944.728 763.6394 2.547 0.013 418.7167 3470.739 reprec1 | -1433.012 1675.361 -0.855 0.396 -4780.955 1914.93 reprec2 | -1117.349 814.6588 -1.372 0.175 -2745.314 510.6168 reprec3 | -396.5179 349.24 -1.135 0.261 -1094.418 301.3826 reprec4 | 332.1495 491.956 0.675 0.502 -650.9461 1315.245 reprec5 | 1611.06 733.4134 2.197 0.032 145.4504 3076.67 - ----------------------------------------------------------------------------- > -
Saved Results - ------------- ^S_E_b^ a matrix containing the grand mean and difference from the mean estimates. ^S_E_se^ a matrix containing the standard errors of the estimates.
Author - ------
Vince Wiggins StataCorp. vwiggins@@stata.com
Also see - --------
Manual: ^[U] 26 Estimation and post-estimation commands^ On-line: help for @lincom@, @predict@, @test@, @testnl@