( after getting confirmation of lack of posts try again, LOL )
---------------------------------------- > From: marchy...@hotmail.com > To: r-help@r-project.org > Subject: RE: [R] Using t tests > Date: Sun, 10 Jul 2011 10:13:51 -0400 > > > ( sorry if this is a repost but I meant to post to list and never received > any indication it was sent to the list, thanks asking for comments about > approach > to data analysis). > > > > From: marchy...@hotmail.com > > To: j...@bitwrit.com.au; gwanme...@aol.com > > CC: r-help@r-project.org > > Subject: RE: [R] Using t tests > > Date: Sun, 10 Jul 2011 07:35:32 -0400 > > > > > > > > > > > > ---------------------------------------- > > > Date: Sat, 9 Jul 2011 18:40:43 +1000 > > > From: j...@bitwrit.com.au > > > To: gwanme...@aol.com > > > CC: r-help@r-project.org > > > Subject: Re: [R] Using t tests > > > > > > On 07/08/2011 07:22 PM, gwanme...@aol.com wrote: > > > > Dear Sir, > > > > > > > > I am doing some work on a population of patients. About half of them are > > > > admitted into hospital with albumin levels less than 33. The other half > > > > have > > > > albumin levels greater than 33, so I stratify them into 2 groups, x and > > > > y > > > > respectively. > > > > > > > > I suspect that the average length of stay in hospital for the group of > > > > patients (x) with albumin levels less than 33 is greater than those with > > > > albumin levels greater than 33 (y). > > > > > > > > What command function do I use (assuming that I will be using the chi > > > > square test) to show that the length of stay in hospital of those in > > > > group x is > > > > statistically significantly different from those in group y? > > > > > > > Hi Ivo, > > > Just to make things even more complicated for you, Mark's suggestion > > > that the length_of_stay measure is unlikely to be normally distributed > > > might lead you to look into a non-parametric test like the Wilcoxon (aka > > > > ( please correct any of the following which is wrong, but note that > > the discusion is more interesting and useful with details of your goals ) > > I'm curious why people still jump to setting arbitrary cutoff points, > > in this case based on what you happen to have sampled, rather than > > try to find a functional relationship between the two parametric > > variables? Generally the thing that separates likely cause from > > noise is smotthness or something you can at least rationalize > > in terms of physical mechanisms. If your question relates > > to the reprodiciblity of a given result (" well this experiment showed > > hi and low were significantly different on hospital stays, maybe the next > > experiement will show the same ") you'd probably like to consider > > the data in relation to possible causes. I'd not sure your disease process > > would know about your median test results when patients walk in. BTW, > > what is terminating the hospital stay, cure death or insurance exhaustion? > > This sounds like you are just trying to reproduce something that is already > > in the literature:cutoff is on the low side of normal and often hypoprotein > > is suspected of being bad, that the higher group would be usually expected > > to do better no? Although > > I suppose this could have something to do with dehydration etc but the point > > of course is that data interpretation is difficult to do in a vacuum. > > > > > > > > > > > > > > > > > > > Mann-Whitney in your case) test. You will have to split your > > > length_of_stay measure into two like this (assume your data frame is > > > named "losdf"): > > > > > > albumin_hilo <- albumin > 33 > > > wilcox.test(losdf$length-of-stay[albumin_hilo], > > > losdf$length_of_stay[!albumin_hilo]) > > > > > > or if you use wilcox_test in the "coin package: > > > > > > albumin_hilo <- albumin > 33 > > > wilcox_test(length_of_stay~albumin_hilo,losdf) > > > > > > Do remember that the chi-square test is used for categorical variables, > > > for instance if you dichotomized your length_of_stay into less than 10 > > > days or 10 days and over. > > > > > > Jim > > > > > > ______________________________________________ > > > R-help@r-project.org mailing list > > > 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. > > > ______________________________________________ R-help@r-project.org mailing list 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.