If I understood your question
x<-data.frame(matrix(rnorm(2000,10,10),ncol=50))
sapply(1:5,function(i) summary(lm(x[,i]~x[,i+10]+x[,50])))
Weidong Gu
On Thu, Jul 14, 2011 at 2:27 PM, Jon Toledo <tintin...@hotmail.com> wrote:
>
> Hi,
> First let me thank you for the incredible help and resource that this forum
> is.
> I am trying to compare the repeated measurement of more than 100 analytes
> that have been take in 70 subjects at 2 time points adjusted for the time
> difference of sample times(TimeDifferenceDays), therefore I wanted to do it
> with a function that allows me to do all at once. (131 is the column
> difference that separates the two different measurements of the same anlyte)
> I have this one:
> for(i in 1:125){return(summary(lm(Data[,i] ~ Data[,(i+131)] +
> Data$TimeDifferenceDays)))}
> But it only gives me one result
>
> I also wanted to get the p-value in a dataframe with three columns:
> Fitst column: analyte name (that愀 the name of the column)Second column:
> pvalue of the first measure of the analte predicting the second measureThird
> column: The effect of time
>
> I copy a samller example:
>
>
> txt <- "V1a V2a V3a V1b V2b V3b TimeDifferenceDays2.42 72.4 3.75 2.46
> 55.4 4.44 6081.66 89.7 2.54 2.17 94.0 2.15 4192.45 112. 0.46 2.40 129.0 .42
> 7142.58 55.6 5.05 2.44 135.0 5.39 7212.61 332.0 22.6 3.55 238.0 16.4 729"
> Data <- read.table(textConnection(txt), header = TRUE)
> Thank you
> Jon Toledo, MD
>
> Postdoctoral fellow
> University of Pennsylvania School of Medicine
> Center for Neurodegenerative Disease Research
>
>
> [[alternative HTML version deleted]]
>
>
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>
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