similar to: 2 Sample Confidence Interval - Formatting Data?

Hello all, I'm trying to graph a scatterplot of a large (5,000 x,y coordinates) of data with the caveat that many of the data points overlap with each other (share the same x AND y coordinates). In using the usual "plot" command, > plot(education, xlab="etc", ylab="etc") it seems that the overlap of points is not shown in the graph. Namely, there are

Hello all, I seem to be having a problem importing a data set from Excel into R. I'm using the "read.table" command to import the data with the following line of code: > newborn<-read.table("newborn edit.csv", header=T, sep=",") where "newborn edit.csv" is the name of the file. Unfortunately, I'm getting back the following error message:

Hello all, I was wondering if anyone knew how to construct a multiple line graph on R, where there are 2 (or more) sets of data points plotted against some x axis of data, and you can draw a line on the graph connecting each set of data points. For example: A B C D 0.6566 2.1185 1.2320 5 0.647 2.0865 1.2325 10 0.6532

Hello, I am doing a simple linear regression analysis that includes few variables. I am using a bootstrap analysis to obtain the variation of my variables to replacement. I am trying to obtain the coefficients 95% confidence interval from the bootstrap procedure. Here is my script for the bootstrap: N = length (data_Pb[,1]) B = 10000 stor.r2 = rep(0,B) stor.r2 = rep(0,B) stor.inter =

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Hi list, is there any direct way to obtain confidence intervals for the regression slope from lm, predict.lm or the like? (If not, is there any reason? This is also missing in some other statistics softwares, and I thought this would be quite a standard application.) I know that it's easy to implement but it's for explanation to people who faint if they have to do their own programming...

Hello all, I'm currently using R to do PCA Analysis, and was wondering if anyone knew the specific R Code that could limit the output of the PCA Analysis so that you only get the Principal Component features as your output and none of the extraneous words or numbers that you don't want. If that was unclear, let me use linear regression as an example: "lm(y~x)" is the normal

Hi, I have a question about the computation of confidence intervals in the zyp package, in particular using the functions zyp.sen and confint.zyp, or zyp.yuepilon. (1) I'm a bit confused about the confidence intervals given by zyp.sen and confint.zyp. When I request a certain confidence interval in the function, the R output seems to deliver another confidence interval, e.g. when I set

Dear R users this may be a simple question - but i would appreciate any thoughts does anyone know how you would get one lower and one upper confidence interval for a set of data that consists of proportions. i.e. taking a usual confidence interval for normal data would result in the lower confidence interval being negative - which is not possible given the data (which is constrained between

Hi, I'm trying to get confidence intervals to slopes from a linear model and I can't figure out how to get at them. As a cut 'n' paste example: ################# # dummy dataset - regression data for 3 treatments, each treatment with different (normal) variance x <- rep(1:10, length=30) y <- 10 - (rep(c(0.2,0.5,0.8), each=10)*x)+c(rnorm(10, sd=0.1), rnorm(10,

Please forgive a rather na??ve question... Could someone please give a quick explanation for the differences in conf intervals achieved via confint.glm (based on profile liklihoods) and the intervals achieved using the Design library. For example, the intervals in the following two outputs are different. library(Design) x = rnorm(100) y = gl(2,50) d = data.frame(x = x, y = y) dd = datadist(d);

List, Would someone be so kind as to point me to a function that will calculate simultaneous confidence intervals of regression coefficients based upon their distribution as (under the assumption of normal errors, with \mathbf{X} as the design matrix): $\hat{\mathbf{\beta}} \sim N(\mathbf{\beta}, \sigma^2(\mathbf{X}^T\mathbf{X})^{-1})$. 'confint' calculates individual coefficients so

I've built a poisson regression model for multiple subjects by using the GLMER function. I've also developed some curves for defining its limits but I did not succeed in developing confidence interval for the model's curve (confint or predict does not work - only for glm). Does anyone know how can I produce confidence interva for a glmer model? I'll appriciate any help... Liat --

Hi, I am attempting to set the confidence limits on a ls means plot as follows: mult<-glht(lm(effectModel, data=statdata, na.action = na.omit), linfct=mcp(mainEffect="Means")) meanPlot <- sub(".html", "meanplot.jpg", htmlFile) jpeg(meanPlot) plot(mult, main=NA, xlab=unlist(strsplit(Args[4],"~"))[1]) This produces 95% CIs by default but I would

Is there an existing function to compute Cook-Weisberg confidence curves for non-linear model parameters in R? Kari Ruohonen -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !)

Hi all! I'm getting a model fit from glm() (a binary logistic regression fit, but I don't think that's important) for a formula that contains powers of the explanatory variable up to fourth. So the fit looks something like this (typing into mail; the actual fit code is complicated because it involves step-down and so forth): x_sq <- x * x x_cb <- x * x * x x_qt <- x * x * x

Dear *, I would like to obtain for each factor of my anova model the "response variable vs factor" plot with means and 95% Tukey HSD intervals. I would appreciate any information on how to do that. Cheers -------------------------------------------------------------------- Max MANFRIN Tel.: +32 (0)2 650 3168 IRIDIA - CoDE, CP 194/6

Hi R People: If I have a fitted values from a model, how do I plot the (1-alpha)100% confidence intervals along with the fitted values, please? Also, if the intervals are "shaded" gray, that would be nice too, please? I check confint, but that doesn't seem to do what I want. Thanks in advance, Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and

Hi there, I have fitted a sample (with size 20) to a normal and/or logistic distribution using fitdistr() in MASS or fitdist() in fitdistrplus package. It's easy to get the parameter estimates. Now, I hope to report the confidence interval for those parameter estimates. However, I don't find a function that could give the confidence interval in R. I hope to write a function, however,

Hi everyone, apologies if the answer to this is in an obvious place. I've been searching for about a day and haven't found anything.. I'm trying to replicate Stata's confidence intervals in R with the survey package, and the numbers are very very close but not exact. My ultimate goal is to replicate Berkeley's SDA website with R (http://sda.berkeley.edu/), which seems to