st: Reganat command in Stata Journal (2013) 13 #1

[Daljit Dhadwal <ddhadwal@gmail.com>]

I was working through the example (on page 105) from the article
Regression anatomy, revealed in Stata Journal Vol 13 #1 page 92-106,
and I’m getting different output than in the article when I use the
semip option. The partial correlation information is displayed but the
semipartial correlation information and the model's variance
decomposition information is missing from the table.

When I issue the following commands in Stata 10.1:

sysuse auto
reganat price length mpg weight, dis(length) semip

I get the following output:

Regression Anatomy
------------------------------------------------------------------------------
Dependent variable ...... : price
Independent variables ... : length mpg weight
Plotting ................ : length
(obs=74)
Partial correlation of price with
    Variable |    Corr.     Sig.
-------------+------------------
      length |  -0.3009    0.010
         mpg |  -0.1226    0.305
      weight |   0.4080    0.000

Model's variance decomposition                            Value          Perc.
------------------------------------------------------------------------------
Variance explained by the X's individually             .              .
Variance common to X's                                         .              .
------------------------------------------------------------------------------
Variance explained by the model (R-squared)              0.3574

Whereas in the article on page 105, the following output is displayed:

Regression Anatomy
------------------------------------------------------------------------------
Dependent variable ...... : price
Independent variables ... : length mpg weight
Plotting ................ : length
(obs=74)

Partial and semipartial correlations of price with

Variable  Partial Corr.  Semipartial Corr.  Partial Corr.^2
Semipartial Corr.^2  Significance Value
length  -0.3009  -0.2530  0.0906  0.0640  0.0102
mpg  -0.1226  -0.0991  0.0150  0.0098  0.3047
weight  0.4080   0.3582   0.1664  0.1283  0.0004

Model´s variance decomposition   Value   Perc.
Variance explained by the X´s individually  0.2021   0.5656
Variance common to X´s    0.1553   0.4344
Variance explained by the model (R-squared)  0.3574

So basically when I use the semip option, I’m missing the semipartial
correlations and the model’s variance decomposition values.

Any help with this would be appreciated.

Thanks,

Daljit Dhadwal

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