Ok. Will do thank you. I do apologize for the spam. That was done in error. On Feb 21, 2016 12:10 AM, "Bert Gunter" <bgunter.4...@gmail.com> wrote:
> Sorry, but please do not multiple post. That's spam. > > This is a list about the R programming language, not about statistical > methods. While there is often some overlap, your questions are entirely > statistical and therefore OT here( at least imo). Try a statistical list > like stats.stackexchange.com instead. > > Cheers, > Bert > > > > On Saturday, February 20, 2016, Virendra Mishra <virendra.mis...@gmail.com> > wrote: > >> Hi R-users, >> >> I have a fairly simple question to ask but I havent yet got an answer to >> the question. I will describe my experiment, analysis and what have I done >> and what is the question in the following paragraphs and I would >> appreciate >> if anyone could point me to use right statistical tools to answer my >> question. >> >> Experiment: >> I have 2 groups and both groups undergo 2 set of evaluations, one with MRI >> scanner and the other in the lab to test for their behavior. Both these >> evaluations are known to have statistically significant relationship with >> age and gender. >> >> Statistical question of interest: >> Whether there is: >> 1) statistically significant difference between the 2 groups on each >> evaluation ? >> 2) Whether there is any relationship between and within the 2 groups >> between each evaluation >> >> Model: >> >> I model the problem as following: >> MRI_measure = Intercept + Slope1 * Age + Slope 2 * Gender + Slope3 * Group >> [Age is continuous and gender , Group are factors/categorical] >> >> Lab_measure = Intercept + Slope1 * Age + Slope 2 * Gender + Slope3 * Group >> [Age is continuous and gender , Group are factors/categorical] >> >> In order to obtain the solution in R: >> MRI_model<-lm(cbind(MRI_measure, Lab_measure) ~ age+gender+group, >> data=data) >> >> Result of R: >> manova(MRI_model) suggests that yes indeed all the slopes are >> significantly >> different than 0 suggesting a relationship between my measures. >> >> Question: >> 1) In order to test whether the difference in the MRI_measure is >> statistically significant different between the 2 groups, I use >> MRI_model$fitted.values for each dependent measure and do a statistical >> test (either t-test or Wilcox) and claim that the difference is >> significant. >> In the paper I write, multivariate multiple linear regression was >> performed >> for the groups while controlling for age and gender. The regressed out >> MRI_measure was statistically compared to see if the difference is >> different. >> >> I am assuming that the predicted/fitted.values in model are the regressed >> out variables. Can I show this and use this result? Is this right >> >> If no, what is the correct way to statistically compare whether my 2 >> groups >> differ in their MRI measure and lab measure when controlled for age and >> gender. Any R library, literature, possibly a script will be greatly >> appreciated. >> >> 2) I also want to see if there is any relationship between MRI_measure and >> Lab_measure within the group after they are controlled for age and gender. >> What is the correct way to do this in R? >> >> Further, I also want to see if there is any significantly different >> association between the 2 groups for my set of dependent variables. I am >> thinking this can be done: I first find the correlation between 2 >> dependent >> variable in each group and test if this correlation is statistically >> different between the 2 groups? Is this logic right? And if it is, how do >> I >> compare the correlation? If not, what is the right way to do this? Any R >> library, literature, possibly a script will be greatly appreciated. >> >> I do appreciate any reply. >> >> Thanks >> >> Regards >> >> Virendra >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > > -- > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
