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From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: odds ratios and confidence intervals after mlogit with a dummy X |

Date |
Tue, 5 Mar 2013 20:25:35 +0100 |

The fact that mathematically equivalent null hypotheses do not necessarily lead to the same test outcome with non-linear Wald tests is documented in -help testnl-. I would use -lincom- with the -rrr- option. That will exactly reproduce the results as returned by -mlogit-: *------------------- begin example -------------------- sysuse auto, clear recode rep78 1/2=3 replace weight = (weight -3000) / 2000 replace price = (price - 6000) / 1000 // regular interaction effect mlogit rep78 c.price##i.foreign weight, rrr // create the odds ratios of price for foreign cars // using lincom lincom _b[4:price] + _b[4:1.foreign#c.price], rrr // check against -mlogit- without reference category // the results are the same mlogit rep78 c.price#ibn.foreign ibn.foreign weight, nocons rrr *-------------------- end example --------------------- Hope this helps, Maarten On Tue, Mar 5, 2013 at 7:07 PM, Jeremy Reynolds <jeremyr@uga.edu> wrote: > Dear Statalist, > > I would like to calculate odds ratios and associated confidence > intervals after a multinomial logit that involves an interaction > between a dummy variable and a continuous variable along with other > covariates. The confidence intervals for the different levels of the > continuous variable are important because the dummy variable has a > negative sign and the interaction a positive sign. I would like to > determine when the dummy variable decreases and and when it increases > the odds of one outcome in the mlogit. > > Drawing on posts to the statalist and Martin Buis' website > (http://www.maartenbuis.nl/publications/interactions.html > ), I have written code to calculate the odds ratios associated with > the dummy variable for different levels of the continuous variable > (please see below). > > However, there appear to be two potential problems with this approach. > > First, nlcom tests whether the odds ratios are different from zero. I > have subtracted 1 from the odds ratio to get the equivalent of testing > whether it is different from 1, but the help file for nlcom makes me > wonder if this procedure is appropriate. > > From the help file for nlcom: > "For instance, the two hypotheses > H0: coefficient = 0 > H0: exp(coefficient) - 1 = 0 > are mathematically equivalent expressions but do not yield the same > test statistic and p-value." > > Second, exchanges on the statalist have suggested that the confidence > intervals calculated by nlcom may not be the what I want: > http://www.stata.com/statalist/archive/2011-12/msg00389.html > > I would be grateful to hear recommendations regarding how to calculate > the odds ratios I want. > > Is the approach in the code below okay? > > Should I use the margins command instead? > When I have seen people use the margins command to get odds and then > calculate odds ratios, they have been working with interactions > between dummy variables and logistic regression. > For example: http://www.stata.com/statalist/archive/2011-05/msg00776.html > > I am not sure how to use margins with a dummy X continuous interaction > and a mlogit model where I must specify which outcome I want. The use > of expression(exp(xb())) for getting the odds seems to preclude the > use of the predict() option that is used to specify which outcome to > use. > > Thanks, > > Jeremy > > > > ****************** > *mlogit with binary by continuous interaction > *slightly modified from example posted at > http://www.stata.com/statalist/archive/2010-10/msg00149.html > ***************** > sysuse auto, clear > > // create an indicator variable that is > // 1 when an observation has valid values > // on mpg, price, and rep78, and 0 otherwise > gen byte touse = !missing(mpg, price, rep78) > > // center mpg > sum mpg if touse, meanonly > gen c_mpg = mpg - r(mean) > > // center price and change unit to 1000s of $ > sum price if touse, meanonly > > *recode price so cheapest car =0 > gen c_price = (price - r(min))/1000 // I have changed this line to > subtract the min rather than the mean > sum c_price > > // see the example FAQ > recode rep78 1/2 = 3 > gen byte baseline = 1 > > // add value labels to rep78 > label define rep78 3 "Average" /// > 4 "Good" /// > 5 "Excellent" > label value rep78 rep78 > > // the model > mlogit rep78 foreign##c.c_price c_mpg baseline, rrr nocons // the > original post had an interaction between c_mpg and c_price > > *calculate odds ratio for foreign (outcome=Good) with 1,000-9,000 > increases in price > sum c_price if e(sample) > foreach x of numlist 1/9 { > di "Odds Ratio for foreign with a `x' thousand dollar increase in price." > nlcom exp(_b[Good:1.foreign])*exp(_b[Good:1.foreign#c.c_price])^`x' - 1 > } > > > -- > ******************** > Dr. Jeremy Reynolds > Associate Professor > Undergraduate Coordinator > Department of Sociology > 117 Baldwin Hall > University of Georgia > Athens, GA 30602-1611 > Phone: (706) 583-8072 > Web: http://uga.edu/soc/people/faculty/reynolds_jeremy.php > Fax: (706) 542-4320 > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ -- --------------------------------- Maarten L. Buis WZB Reichpietschufer 50 10785 Berlin Germany http://www.maartenbuis.nl --------------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: odds ratios and confidence intervals after mlogit with a dummy X***From:*Jeremy Reynolds <jeremyr@uga.edu>

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