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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: AW: re: beta coefficients for interaction terms |

Date |
Sun, 21 Jun 2009 16:23:04 +0200 |

<> " so it is not telling you anything for which you need to estimate the regression to find out." So the point estimate is equal to ouput of other commands, bout how about the CI? ************* sysuse auto, clear egen shead = std(headroom) egen slength = std(length) gen ia2 = shead*slength egen sia2 = std(ia2) /*compare */ reg mpg shead slength sia2 mean mpg ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Kit Baum Gesendet: Sonntag, 21. Juni 2009 15:59 An: statalist@hsphsun2.harvard.edu Betreff: st: re: beta coefficients for interaction terms <> Lisa said but it is important for my paper to show the value of the intercept, and I get different values if I use either the standardized or the not standardized dependent variable. If I have the null hypothesis that is is equal to zero, do I have to use the standardized or not standardized dependent variable? And coming back to my original question: Why do I have to standardize the dependent variable? and in fact if you do standardize both dep and indep vars as suggested by an earlier post, the constant term is by definition zero. The regression surface passes through the multivariate point of means, and that is now (0,0,0,0,0). When you do run the regression of *un*standardized dep var on standardized regressors as you would now like to do, the constant term is by construction the *un*conditional mean of the dep var: . reg mpg shead slength sia2 Source | SS df MS Number of obs = 74 -------------+------------------------------ F( 3, 70) = 41.45 Model | 1563.44248 3 521.147494 Prob > F = 0.0000 Residual | 880.016979 70 12.5716711 R-squared = 0.6398 -------------+------------------------------ Adj R-squared = 0.6244 Total | 2443.45946 73 33.4720474 Root MSE = 3.5457 ---------------------------------------------------------------------------- -- mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------- +---------------------------------------------------------------- shead | -.1288064 .4934882 -0.26 0.795 -1.113038 .8554248 slength | -4.598606 .4846015 -9.49 0.000 -5.565113 -3.632098 sia2 | .4815198 .4260752 1.13 0.262 -. 3682604 1.3313 _cons | 21.2973 .4121741 51.67 0.000 20.47524 22.11935 ---------------------------------------------------------------------------- -- . end of do-file . su mpg Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- mpg | 74 21.2973 5.785503 12 41 so it is not telling you anything for which you need to estimate the regression to find out. Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html * * 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/ * * 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/

**References**:**st: re: beta coefficients for interaction terms***From:*Kit Baum <kitbaum@mac.com>

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