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

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

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

Date |
Tue, 21 Apr 2009 15:49:32 +0200 |

<> You either standardize yourself, and use the normal -regress- command, or let Stata do the work with the -beta- option, but not both at the same time... ************* sysuse auto, clear reg pr we tr tu, beta foreach var of varlist pr we tr tu{ egen std`var'=std(`var') } reg stdpr stdwe stdtr stdtu ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von lschoele@rumms.uni-mannheim.de Gesendet: Dienstag, 21. April 2009 15:38 An: statalist@hsphsun2.harvard.edu Betreff: Re: AW: st: AW: beta coefficients for interaction terms Hi, I have another question regarding beta coefficients: After coding: . sysuse auto, clear . egen shead = std(headroom) . egen slength = std(length) . egen smpg = std(mpg) . gen ia2 = shead*slength . egen sia2 = std(ia2) . reg smpg shead slength sia2 Do I have to do .regress, beta? Without having iteraction terms, as far as I know you have to coed .regress, beta to get the standardised beta coefficients, so you can tell which variable has the biggest effect. Thank you Lisa Zitat von Ulrich Kohler <kohler@wzb.eu>: > I think Lisa refer the section on standardized regression cofficients of > that book, particularly to the second item on pg. 201 (English edition). > That item states that one should not use b*s_x/s_y to create > standardized regression coefficients in the presence of interaction > terms. Based on Aiken/West 1991 (28-48) it is recommended that one > should standardize all variables that are part of the interaction in > advance. Hence, instead of coding > > . sysuse auto, clear > . gen ia = head*length > . reg mpg head length ia, beta > > you should code > > . sysuse auto, clear > . egen shead = std(headroom) > . egen slength = std(length) > . egen smpg = std(mpg) > . gen ia2 = shead*slength > . egen sia2 = std(ia2) > . reg smpg shead slength sia2 > > The estimated coefficients of the constituent effects then show how much > standard deviations the dependend variable change when the independent > variable changes by one standard deviation and the other variable of the > interaction term is at its mean. > > Standardized regression coefficients are often used to find out which of > the independent variables have the "largest" effect. I must admit that I > often fail to understand why students want to know that. But leaving > that aside, if an effect is not constant over the range of another > variable (i.e. in the presence of an interaction term) the question of > which independent variable have the largest effect seems pointless. > > > Many regards > Uli > > > Am Donnerstag, den 16.04.2009, 14:47 +0200 schrieb Martin Weiss: >> <> >> >> Your -gen- statement computes the interaction, but Stata would treat this >> new variable as a covariate in its own right, w/o any connection to other >> covariates. A similar issue arises with quadratic terms of a covariate >> (http://www.stata.com/statalist/archive/2008-08/msg00307.html). >> >> >> The book you mentioned has a subsection on the topic on pages 222-226, and >> the English version seems to be a straightforward translation of it, AFAIK >> (http://www.stata-press.com/books/daus2.html, page 222). I cannot find the >> stuff on the beta coefficient there, though. They do say that you should >> check for missings with -rowmiss- and that you should subtract the mean from >> the variables before standardization. The latter is easily accomplished via >> >> ***** >> sysuse auto, clear >> >> *enter your vars to be standardized here >> local stdvars "price weight trunk turn" >> >> foreach var of local stdvars{ >> summ `var', mean >> gen std`var'=`var'-r(mean) >> } >> ***** >> >> -egen, std()- would divide by the standard deviation in addition to my >> code... >> >> HTH >> Martin >> >> >> -----Ursprüngliche Nachricht----- >> Von: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von >> lschoele@rumms.uni-mannheim.de >> Gesendet: Donnerstag, 16. April 2009 14:07 >> An: statalist@hsphsun2.harvard.edu >> Betreff: Re: st: AW: beta coefficients for interaction terms >> >> How do I tell stata, that it is an inetraction term? >> Here is what I did: >> gen appearance_attention=apperance*attention >> >> Is that telling stata, that the new variable is an interaction term? >> >> I am referring to the book "Datenanalyse mit Stata" by Kohler, Kreuter >> >> "Note that you can effect the standardization yourself via - egen, >> std()-" What standardization do you mean? The z-standardization or the >> "normal" standardization for the beta coefficients, that I need for >> the interpretation? >> >> Best Lisa >> >> >> Zitat von Martin Weiss <martin.weiss1@gmx.de>: >> >> > <> >> > >> > Well, did you tell Stata in any way that a specific variable is an >> > "interaction term"? If not, Stata probably treats it as just another >> > covariate in your regression. >> > >> > BTW, which book are you referring to? >> > >> > Note that you can effect the standardization yourself via - egen, std()- >> > >> > >> > HTH >> > Martin >> > >> > -----Ursprüngliche Nachricht----- >> > Von: owner-statalist@hsphsun2.harvard.edu >> > [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von >> > lschoele@rumms.uni-mannheim.de >> > Gesendet: Donnerstag, 16. April 2009 12:35 >> > An: statalist@hsphsun2.harvard.edu >> > Betreff: st: beta coefficients for interaction terms >> > >> > Hi Statalist, >> > >> > I am working on a regression model with interactions between some >> > variables. I read in a book, that I can't use the "normal" >> > standardized beta coefficients for the interaction terms. They said >> > that the interpretation of the beta coefficients is not possible until >> > you z-standardise the interaction variables before you do the >> > regression. >> > >> > Does anyone know, if stata does the z-standardization for the >> > interaction variables automatically, so I can use the normal >> > standardized beta coefficients (shown in the stata output) for the >> > interpretation? >> > I am using the 9.1 version of stata. >> > >> > I hope someone can help me. >> > >> > Best Lisa >> > >> > * >> > * 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/ >> > >> > >> >> >> >> * >> * 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/ > -- > kohler@wzb.eu > 030 25491-361 > > > * > * 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/ * * 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: beta coefficients for interaction terms***From:*lschoele@rumms.uni-mannheim.de

**st: AW: beta coefficients for interaction terms***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**Re: st: AW: beta coefficients for interaction terms***From:*lschoele@rumms.uni-mannheim.de

**AW: st: AW: beta coefficients for interaction terms***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**Re: AW: st: AW: beta coefficients for interaction terms***From:*Ulrich Kohler <kohler@wzb.eu>

**Re: AW: st: AW: beta coefficients for interaction terms***From:*lschoele@rumms.uni-mannheim.de

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