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From |
"Mona Mowafi" <mmowafi@hsph.harvard.edu> |

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

Subject |
Re: st: age-adjusted means |

Date |
Mon, 25 Aug 2008 09:02:07 -0400 |

Thank you for your response, Maarten. I forgot to mention, I do have the continuous BMI variable, so I would not have to assign values separately. But I cannot do an ANOVA and then get the means b/c I violate ANOVA/regress assumptions of normality.. I am getting predicted probabilities by using multinomial for a separate table, but I thought a simple table of age-adjusted means would be helpful as well.. I will look up the commands you spoke of, but just wanted to throw that out there in case these commands don't work for this purpose.. Many thanks, Mona >>> Maarten buis <maartenbuis@yahoo.co.uk> 8/25/2008 2:07 AM >>> --- Mona Mowafi <mmowafi@hsph.harvard.edu> wrote: > I need to get the age-adjusted means of my outcome (3 categories of > BMI: normal weight, overweight, obese) on each of my independent > variables (indicators of SES), but my data is very non-normally > distributed (over 50% of sample is obese) and I am conducting > multinomial regression in my analyses. If you want a mean than you will have to assign numeric values to each category of your depedent variable, and those numeric values have to mean something: For instance in case of a variable religion you can give the value 1 to christian, 2 to muslim, and 3 to other, and than compute the mean of the variable religion, but that does not mean anything. Similarly, you can assign 1 to normal weight, 2 to overweight, and 3 to obese, but what does that mean? Probabily a bit more than the religion example (as this ordering corresponds with the natural ordering of that variable), but not much: Why would the distance between normal and overweight be exactly the same as the distance between overweight and obese? If you are using multinomial regression the natural thing to look at is not the mean of the outcome, but the probabilities of ending up in each category of the outcome. A very helpful tool is the -prgen- command which is part of the -spost-, which you can download by typing -findit spost-. This command is discussed in the following Stata Journal article: Jun Xu and J. Scott Long (2005) "Confidence intervals for predicted outcomes in regression models for categorical outcomes" The Stata Journal, 5(4): 537--559. http://www.stata-journal.com/article.html?article=st0094 Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- Send instant messages to your online friends http://uk.messenger.yahoo.com * * 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/

**Follow-Ups**:**st: matching databases***From:*kokootchke <kokootchke@hotmail.com>

**References**:**st: age-adjusted means***From:*"Mona Mowafi" <mmowafi@hsph.harvard.edu>

**Re: st: age-adjusted means***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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