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From |
Robson Glasscock <glasscockrc@vcu.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Correlation between 2 variables overtime- accounting for repeated measures |

Date |
Sun, 17 Mar 2013 11:22:32 -0400 |

I am going to refer to a as y and b as x in this post. If I’m understanding you correctly, you want to estimate the relationship between y and x. You are not really interested in the relationship between y and the surgery, and you don’t think that the effect of x on y changed based on the surgery or over time. I also know you said originally that you wanted the correlation, but I’m going to approach this using regression and a panel data setup. It also sounds like the jury is still out on whether the fixed effects transformation is appropriate for your research question. I think the following model with standard errors adjusted for correlation in the error term by individual (subject to the discussion below) is similar to what you are trying to estimate. Surg is a dummy variable equal to 1 in year 2 and year 3, else 0. Year_2 is a dummy variable equal to 1 in year 2, else 0. Year 3 is a dummy variable equal to 1 in year 3, else 0. y= B0 + B1(x) + B2(surg) + B3(year_2) + B4(year_3) + e This model estimates marginal effect of x on y and controls for the influences of both surgery and time. However, this model cannot be estimated because surg is a linear function of year_2 and year_3 (i.e. surg= year_2 + year_3). I think this leaves you with two options. The first is to treat the two post-surgery years as one period: y= Bo + B1(x) +B2(surg) + e I am less confident with the second option, but I think depending on your assumptions about how the distribution of y changes over time, that you can include a trend term in the model. The trend variable equals 1 in year 1, 2 in year 2, 3 in year 3. y= B0 + B1(x) + B2(surg) + B3(trend) + e I would like to hear from others if my reasoning is flawed on including the trend in the model. Lastly, depending on your assumptions about fixed effects, you could estimate the above models with -reg, cluster(individual)- or -xtreg, fe- best, Robson Glasscock On Sat, Mar 16, 2013 at 7:46 PM, JVerkuilen (Gmail) <jvverkuilen@gmail.com> wrote: > On Sat, Mar 16, 2013 at 6:49 PM, megan rossi <megan_rossi@msn.com> wrote: >> Yes The surgery was 1-3weeks after the baselines were taken...a fairly strict protocol. Then one year follow up and two year follow up...variable a &b were both low at baseline (still detectable and possibly correlated) but rise following surgery so are high at year 1 and year 2...perhaps best to just combine year 1 and 2 as if they're both high a correlation would be easier to find then if they're both low? >> > > I don't think I'd combine them. You have different measures and that > should be respected. > > To me the fact that this is longitudinal means that there's a clear > logical priority. I'd consider the first measurement as "causal" of > the second one, at least in some respect. So I'm not sure a pure > correlation makes sense. But I'd like to hear what others might say. > > * > * 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/ * * 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/

**Follow-Ups**:**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*David Hoaglin <dchoaglin@gmail.com>

**References**:**st: Correlation between 2 variables overtime- accounting for repeated measures***From:*megan rossi <megan_rossi@msn.com>

**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*megan rossi <megan_rossi@msn.com>

**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*megan rossi <megan_rossi@msn.com>

**Re: st: Correlation between 2 variables overtime- accounting for repeated measures***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

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