Hi:
When it comes to split, apply, combine, think plyr.
library(plyr)
ldply(split(afvtprelvefs, afvtprelvefs$basestudy),
function(x) coef(lm (ef ~ quartile, data=x, weights=1/ef_std)))
.id (Intercept) quartile
1 CBP0908020 20.92140 3.38546887
2 CBP0908021 29.31632 0.01372604
3 CBP0908022 39.10000 3.30000000
ldply() takes a list as input and outputs a data frame. Like lapply, the
first argument is the list and the second argument is the apply function.
HTH,
Dennis
On Tue, Oct 26, 2010 at 10:22 AM, Small Sandy (NHS Greater Glasgow & Clyde)
<sandy.sm...@nhs.net> wrote:
> Thanks David
> That's great
>
> As a matter of interest, to get a data frame by studies why do you have to
> do
>
> fitsdf <- as.data.frame(t(as.data.frame(fits)))
>
> Why doesn't
> fitsdf <- as.data.frame(t(fits))
> work?
>
> Sandy Small
>
> ________________________________________
> From: David Winsemius [dwinsem...@comcast.net]
> Sent: 26 October 2010 16:37
> To: Small Sandy (NHS Greater Glasgow & Clyde)
> Cc: r-help@r-project.org
> Subject: Re: [R] Forcing results from lm into datframe
>
> On Oct 26, 2010, at 8:08 AM, Small Sandy (NHS Greater Glasgow & Clyde)
> wrote:
>
> > Hi
> >
> > I need some help getting results from multiple linear models into a
> > dataframe.
> > Let me explain the problem.
> >
> > I have a dataframe with ejection fraction results measured over a
> > number of quartiles and grouped by base_study.
> > My dataframe (800 different base_studies) looks like
> >
> >> afvtprelvefs
> > basestudy quartile ef ef_std entropy
> > CBP0908020 1 21.6 0.53 3.27
> > CBP0908020 2 32.5 0.61 3.27
> > CBP0908020 3 30.8 0.63 3.27
> > CBP0908020 4 33.6 0.37 3.27
> > CBP0908022 1 42.4 0.52 1.80
> > CBP0908021 1 29.4 0.70 2.63
> > CBP0908021 2 29.2 0.42 2.63
> > CBP0908021 3 29.7 0.89 2.63
> > CBP0908021 4 29.3 0.50 2.63
> > CBP0908022 2 45.7 1.30 1.80
> > ...
> >
> > What I want to do is apply a weighted linear fit to the results from
> > each base study and get the gradient out of it. I then want to plot
> > the gradient against the entropy (which is constant for each base
> > study).
> >
> > I can get apply a linear fit with
> >
> >> fits <- by(afvtprelvefs, afvtprelvefs$basestudy, function (x) lm
> >> (ef ~ quartile, data=x, weights=1/ef_std))
> >
> > but how do I get the results from that into a dataframe which I can
> > use?
> >
> > I thought I might get somewhere with
> >> sapply(fits, "[[", "coefficients")
> >
> > But that doesn't give me the basestudy separately so that I can
> > match up the results with the entropy results.
>
> The by objects don't play nicely with as.data.frame so I went to a
> more "classical" way of runnning the lm call and I added a coef()
> wrapper to just get the coefficients:
>
> > splits <-split(afvtprelvefs, afvtprelvefs$basestudy)
> > lapply(splits, function (x) coef(lm (ef ~ quartile, data=x,
> weights=1/ef_std)))
> $CBP0908020
> (Intercept) quartile
> 20.921397 3.385469
>
> $CBP0908021
> (Intercept) quartile
> 29.31632071 0.01372604
>
> $CBP0908022
> (Intercept) quartile
> 39.1 3.3
>
> > fits <- lapply(splits, function (x) coef(lm (ef ~ quartile, data=x,
> weights=1/ef_std)))
> > as.data.frame(fits)
> CBP0908020 CBP0908021 CBP0908022
> (Intercept) 20.921397 29.31632071 39.1
> quartile 3.385469 0.01372604 3.3
>
>
> The split-lapply strategy is reasonably general. You may need to use
> t() if you were hoping for stufy to be by rows. In this case sapply
> would have obviated the need for the as.data.frame step at the cost of
> returning a matrix rather than a data.frame.
> --
> David
>
> >
> > I am sure this must have been answered somewhere before but I have
> > been unable to find a solution.
> > Many thanks for your help
> >
> > Sandy Small
> > NHS Greater Glasgow and Clyde
> >
> >
> >
> ********************************************************************************************************************
> >
> > This message may contain confidential information. If yo...{{dropped:
> > 24}}
> >
> > ______________________________________________
> > 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.
>
>
>
>
> ********************************************************************************************************************
>
> This message may contain confidential information. If ...{{dropped:13}}
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