Martin Weiss made some suggestions.
I have three quite different comments:
1. -correlate- rather than -spearman- is more closely related to
properties affecting multiple regression.
2. With that many variables it is easy to produce a scatter plot matrix
using -graph matrix-. Mentioning the response (dependent variable in
your terms) last means that the last row of the matrix has scatter plots
with the response on the vertical axis:
. graph matrix weight length disp turn mpg
3. -corrci- from Stata Journal 8(3) 2008 offers an alternative to
-correlate-. This is the default display:
. corrci mpg weight length turn disp
(obs=74)
correlations and 95% limits
mpg weight -0.807 -0.874 -0.710
mpg length -0.796 -0.867 -0.693
mpg turn -0.719 -0.814 -0.587
mpg displacement -0.706 -0.804 -0.569
weight length 0.946 0.915 0.966
weight turn 0.857 0.782 0.908
weight displacement 0.895 0.838 0.933
length turn 0.864 0.792 0.913
length displacement 0.835 0.750 0.893
turn displacement 0.777 0.667 0.854
The -ci- stands for confidence interval. -corrci- is dedicated to the
idea that a confidence interval is often superior to a P-value, just as
a P-value is usually superior to stars.
-corrci- thus does not support stars, least of all in a non-standard
scheme like that requested by Bastian (although possibly he did not mean
what he wrote).
I have already vented my spleen against stars on this list, so I won't
repeat that in detail here.
<http://www.stata.com/statalist/archive/2007-03/msg00646.html>
Nick
[email protected]
Bastian Steingros
I want to make a correlation analysis before running some regressions.
I have 4 independent and 1 dependent variable.
Using the command *spearman*, is it possible to use a further command
help me to put the result directly into a table (inclusive the
significance stars * 0.01 ** 0.05)??
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
