Dear Sirs, I am a R beginning user: by mean of R I would like to apply the bootstrap to my data in order to test cost differences between independent or paired samples of people affected by a certain disease. My problem is that even if I am reading the book by Efron (introduction to the bootstrap), looking at the examples in internet and available in R, learning a lot of theoretical things on bootstrap, I can't apply bootstrap with R to my data because of many doubts and difficulties. This is the reason why I have decided to ask the expert for help. I have a sample of diabetic people, matched (by age and sex) with a control sample. The variable I would like to compare is their drug and hospital monthly cost. The variable cost has a very far from gaussian distribution, but I need any way to compare the mean between the two group. So, in the specific case of a paired sample t-test, I aim at testing if the difference of cost is close to 0. What is the better way to follow for that? Another question is that sometimes I have missing data in my dataset (for example I have the cost for a patients but not for a control). If I introduce NA or a dot, R doesn't estimate the statistic I need (for instance the mean). To overcome this problem I have replaced the missing data with the mean computed with the remaining part of data. Anyway, I think R can actually compute the mean even with the presence of missing data. Is it right? What can I do? Thank you very much for your attention and, I hope, your help. Best wishes Luciana Scalone Center of Pharmacoeconomics University of Milan [[alternative HTML version deleted]]
Hi On 13 Jul 2004 at 12:28, luciana wrote:> Dear Sirs, > > I am a R beginning user: by mean of R I would like to apply the > bootstrap to my data in order to test cost differences between > independent or paired samples of people affected by a certain > disease. > > My problem is that even if I am reading the book by Efron > (introduction to the bootstrap), looking at the examples in internet > and available in R, learning a lot of theoretical things on > bootstrap, I can't apply bootstrap with R to my data because of many > doubts and difficulties. This is the reason why I have decided to > ask the expert for help. > > > > I have a sample of diabetic people, matched (by age and sex) with a > control sample. The variable I would like to compare is their drug > and hospital monthly cost. The variable cost has a very far from > gaussian distribution, but I need any way to compare the mean > between the two group. So, in the specific case of a paired sample > t-test, I aim at testing if the difference of cost is close to 0. > What is the better way to follow for that? > > > > Another question is that sometimes I have missing data in my dataset > (for example I have the cost for a patients but not for a control). > If I introduce NA or a dot, R doesn't estimate the statistic I need > (for instance the mean). To overcome this problem I have replaced > the missing data with the mean computed with the remaining part of > data. Anyway, I think R can actually compute the mean even with the > presence of missing data. Is it right? What can I do?your.statistic(your.data, na.rm=T) e.g. mean(your.data, na.rm=T) or look at ?na.action e.g mean(na.omit(your.data)) Cheers Petr Pikal> > > > Thank you very much for your attention and, I hope, your help. > > > > Best wishes > > > > Luciana Scalone > > Center of Pharmacoeconomics > > University of Milan > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.htmlPetr Pikal petr.pikal at precheza.cz
just a hint for further bootstrapping examples (worked out with R): "Bootstrap Methods and Their Applications" by A.C. Davison and D.V. Hinkley cheers christoph luciana wrote:> Dear Sirs, > > I am a R beginning user: by mean of R I would like to apply the bootstrap to my data in order to test cost differences between independent or paired samples of people affected by a certain disease. > > My problem is that even if I am reading the book by Efron (introduction to the bootstrap), looking at the examples in internet and available in R, learning a lot of theoretical things on bootstrap, I can't apply bootstrap with R to my data because of many doubts and difficulties. This is the reason why I have decided to ask the expert for help. > > > > I have a sample of diabetic people, matched (by age and sex) with a control sample. The variable I would like to compare is their drug and hospital monthly cost. The variable cost has a very far from gaussian distribution, but I need any way to compare the mean between the two group. So, in the specific case of a paired sample t-test, I aim at testing if the difference of cost is close to 0. What is the better way to follow for that? > > > > Another question is that sometimes I have missing data in my dataset (for example I have the cost for a patients but not for a control). If I introduce NA or a dot, R doesn't estimate the statistic I need (for instance the mean). To overcome this problem I have replaced the missing data with the mean computed with the remaining part of data. Anyway, I think R can actually compute the mean even with the presence of missing data. Is it right? What can I do? > > > > Thank you very much for your attention and, I hope, your help. > > > > Best wishes > > > > Luciana Scalone > > Center of Pharmacoeconomics > > University of Milan > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > >
Hi On 13 Jul 2004 at 12:28, luciana wrote:> Dear Sirs,> I have a sample of diabetic people, matched (by ageand sex) with a> control sample. The variable I would like to compareis their drug> and hospital monthly cost. The variable cost has avery far from> gaussian distribution, but I need any way to comparethe mean> between the two group. So, in the specific case of apaired sample> t-test, I aim at testing if the difference of costis close to 0.> What is the better way to follow for that? >I can suggest to see: ? pairwise.wilcox.test() ? wilcox.test using non-parametric tests instead of t-test. Cordially Vito ====Diventare costruttori di soluzioni Visitate il portale http://www.modugno.it/ e in particolare la sezione su Palese http://www.modugno.it/archivio/cat_palese.shtml