[R] principal component analysis

Hello, I have used prcomp and the variances for the first 3 PC's are 2.65, 1.97 and 0.38. When I plot the principal component values for each data point I can see that the points lie in a plane as one might expect from the variances. But this plane is diagonal through the 3D space of the first

[R] thickness of tick marks

Hi, I am unable to get the tick marks to appear thicker in plot. I have tried things like par(lw=2) but this only seems to affect other line thicknesses. The use of axes directly fixes the problem because lw = 2 applies to both the axis and the ticks. Is there is way of feeding a single

[R] Getting Pr from Summary(lm)

Hello, I am trying to get the P values from the output of a summary for lm. lm - lm(y ~ age + sex) s - summary(lm) I thought that I might be able to get them using a combination of scan, grep and sub. But I got stuck on the first step - being able to process s as a text string. I could perhaps

Re: [R] Specifying xlevels in effects library

Andy and John, I looked at typical when xlevels did not work but when I saw that it was a function I went no further. Setting the function to a constant was a good idea. John's method seems to require that I change the model: eff -effect(sex*age,mod,xlevel=(Age=c(120,120))) Error in

Re: [R] Getting Pr from Summary(lm)

Thanks for all the relies. I recently discovered names and applied it to lm objects but did not think to apply it to the summary object. Cheers, David __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do

[R] loess prediction limits

Hello I am plotting a loess curve with confidence limits as below. How do I create the prediction limits? Is multiplying the standard errors by sqrt(n) appropriate? data - mndata lo - loess(data[[variableName]] ~ Age, data, span=1.0, control = loess.control(surface = direct)) xPoints -

Re: [R] Getting the same values of adjusted mean and standard errors as SAS

Frank E Harrell Jr wrote: On Thu, 27 May 2004 16:34:58 +0930 David J. Netherway [EMAIL PROTECTED] wrote: Hello, I am trying to get the same values for the adjusted means and standard errors using R that are given in SAS for the following data. The model is Measurement ~ Age + Gender + Group. I can

[R] Getting the same values of adjusted mean and standard errors as SAS

Hello, I am trying to get the same values for the adjusted means and standard errors using R that are given in SAS for the following data. The model is Measurement ~ Age + Gender + Group. I can get the adusted means at the mean age by using predict. I do not know how to get the appropriate

[R] Setting up contrasts

I am using the following model: lm - lm(mydata[[variableName]] ~ Age + Gender + Group, data=mydata) There are 5 groups in Group: nonc (the control), c1,c2,c3 and c4. How do I contrast nonc vs the others? and How do I contrast c1 vs other c's (ie c2,c3,c4 as a subgroup)? I have looked at the