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From |
"Justina Fischer" <[email protected]> |

To |
[email protected] |

Subject |
Re: st: problem with marginal effect after running a logit regression |

Date |
Mon, 30 Jul 2012 02:49:29 +0200 |

Hi Jeremy, please do not forget to thank Rieza in your acknowledgement as she resolved half of your problems of your master thesis. Actually, I do think that with reading of some basic econometrics books + reading the xtensive Stata handbook on margins you should have been able to answer most of these questions all by yourself. Justina -------- Original-Nachricht -------- > Datum: Sun, 29 Jul 2012 18:15:44 -0500 > Von: Rieza Soelaeman <[email protected]> > An: [email protected] > Betreff: Re: st: problem with marginal effect after running a logit regression > Hi Jeremy, > Your advisor is correct that the coefficients of a logistic regression > cannot be interpreted in the same way as OLS. Using the margins > command allows for an estimation of the marginal effect (e.g. the > increase in probability of your outcome = 1, here I assumed outcome is > binary). One question for you: when your advisor meant by "at median," > did he mean at median values for all the characteristics in your > model, or just the median level of education? > > If the specific effect of interest is going from mstudymid to > mstudyhigh, I would suggest making mstudymid the reference category in > your set of dummy variables for education. Here I assume you have > mstudylow as the reference (excluded) category. If you make mstudymid > your reference, then the marginal effect of mstudyhigh would be the > marginal effect of going from mstudymid to mstudyhigh. Similarly, the > marginal effect of mstudylow would be the marginal effect of going > from mstudylow to mstudymid. > > Typically, if your predictors are continuous, it makes sense to have > Stata calculate marginal effects at the means of each value of your > predictors. This can be achieved by executing the following command > after running your regression: > > margins, atmeans > > However, because your predictors are categorical (or if you are using > a version of Stata before Stata 12), you may be able to get away with > specifying criteria for the "typical" individual in your dataset for > which you are calculating the marginal effect. Then justify the > choices you made in describing the "typical" individual. > > For example, in your dataset, the "typical" individual may be a 35 > year old, male, who is a chief wage earner, with high education, > mintpol = "mid", mpol = "right", and mincome = "high," then the > command you would run would be something like: > > mfx, at (mstudymid=0 mstudyhigh=1 mhomme=1 mchiefwageearner=1 mage28_37=1 > mage38_47=0 mage48_57=0 .............. mincomehigh=1) > > *Note the ........... means you should assign a 0 or 1 value for your > categorical predictors as appropriate to describe your person. > > I see there are several variables in your dataset that could benefit > from being continuous, though. If age were continuous, you can simply > plug in the average age (from any of the univariate commands you can > use to describe the mean of a vbl). Same thing with income. I think > it would make your regression more robust to use the continuous. > > Of course using this method (with -mfx-) is complicated by the > clustering in your data and the interactions between the cluster > variables S003 and S002 (it appears to me these are polychotomous > categorical variables, as you have used the i. in adding them to your > regression). Because I don't know what they represent and how many > levels of each they are, I am not sure how they would be specified in > the -mfx- command. Do you absolutely need to know the marginal effect > of each of those clusters, or were they included just so you can > control for them? If you included them just to control for them, > consider using -xtmelogit- (mixed effects logit) instead, and specify > S003 and S002 for random intercept calculation. > > HTH, > Rieza > > *I invite other statalisters to correct me if I have said something in > error > above. > > On Thu, Jul 26, 2012 at 2:17 PM, Jeremy Franklin <[email protected]> > wrote: > > Dear all, > > > > Here is my little trouble: > > > > For my master degree thesis I decided to test for the role of education > level in assession the importance of fighting inflation. > > > > Here is my final regression formula: > > > > xi: logit mfirstchoice mstudymid mstudyhigh mhomme mchiefwageearner > mage28_37 mage38_47 mage48_57 mage58 mintpollow mintpolmid mintpolhigher > mpolleft mpolright mincomemid mincomehigh i.s003 i.s002 i.s003*i.s002, > vce(cluster s003) > > > > I hate the results but my thesis coordinator told me that the results of > logit regression cannot be interpreted like coefficients of a linear > regression. Therefore, he suggested me to check for the marginal effects at the > median in order to see the marginal effects of one individual coming from > mstudymid to mstudyhigh > > > > I googled everything, i tried hundreds of formulas, both with mfx and > margins but i still cannot find the correct one in order to interpret my > results. > > > > Can ANYONE help me please. > > > > ps: a robustness test included in my thesis include the following > formula (this time with ologit)- > > > > xi: ologit minflation mstudymid mstudyhigh mhomme mchiefwageearner > mage28_37 mage38_47 mage48_57 mage58 mintpollow mintpolmid mintpolhigher > mpolleft mpolright x047 i.s003 i.s002 i.s003*i.s002, vce(cluster s003) > > > > * > > * 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/ -- Justina AV Fischer, PhD COFIT Fellow World Trade Institute University of Bern homepage: http://www.justinaavfischer.de/ e-mail: [email protected]. [email protected] papers: http://ideas.repec.org/e/pfi55.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/

**References**:**st: problem with marginal effect after running a logit regression***From:*Jeremy Franklin <[email protected]>

**Re: st: problem with marginal effect after running a logit regression***From:*Rieza Soelaeman <[email protected]>

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