similar to: Variability plot in R

Hi helpeRs, I've been working through some examples in Pinhiero & Bates( 2000) trying to understand how to translate to the new Lme4 syntax but without much luck. Below is what I think I should do, but either the answers don't come out the same or I get errors. In the Oxide problems I'm particularly interested in obtaining the levels coeficients but this options no longer seems

My question relates to problems that I'm having matching lme and lmer examples in P&B. using Matix 0.995 In the Oxide example in p167-170 I can't get the level 2 coefficient estimates to match the fm1Oxide model in lme is data(Oxide,package="nlme") lme(Thickness~1,Oxide) which I translate in Lmer syntax to fm3Oxide<-lmer(Thickness~

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

I've noticed a change in the way grep() behaves between the 1.9.0 release and a recent R-patched. On 1.9.0 I get the following output: > x <- dget(file = url("http://www.biostat.jhsph.edu/~rpeng/names.R")) > length(grep("^l\\w+tmean", x, perl = TRUE, value = TRUE)) [1] 84 And on R-patched (2004-06-11) I get > x <- dget(file =

Hi all, I tried to do a variance components using nlme, but I got the following warning mesage ##################################################### not meaningful for factors in: Ops.factor(y[revOrder], Fitted) ###################################################### Can someone point out what is the meaning of this warning message? I tried to look at Ops.factor, but I don't

I am trying to run the following code in R on a Linux cluster. I would like to use the full processing power (specifying cores/nodes/memory). The code essentially runs predictions based on a GAM regression and saves the results as a CSV file for multiple sets of data (here I only show two). Is it possible to run this code using HPC packages such as Rmpi/snow/doParallel? Thank you!

I am trying to understand the proper way to encode the nesting structure for data in the context of nlme, in the specific case of individuals nested within species for which each individual is unique. I have searched through Pinheiro & Bates and also past postings, but without success. Take the Wafer data set which has 2 levels: Wafer (8 values) and Site nested within Wafer (10 values for

I have one fixed effect, sor, with two levels. I have eight lots and three wafers from each lot. I have included the data below. I would like to fit a mixed model that estimates a covariance parameter for wafer, which is nested in lot, and two covariance parameters for lot, one for each level of sor. The following command fits the model that I want, except for it estimates the correlation

I have a set of time-series climate data with missing entries. I need to add rows for these missing entries to this data set. The only way I know to do this is unsing a foreloop, but this won't work on a list. I've tried to convert the list to a data frame, but that won't happen, either. I want to fill rows in this table: > newtest[10:15,] yrmos yearmo snow.sum snow.mean

Dear All; Attempting to reproduce Figure 4.15 of MEMSS (p. 171) in R using plot(Wafer, outer = ~ Wafer) yields an error: > plot(Wafer, outer = ~ Wafer) Error in order(na.last, decreasing, ...) : Argument lengths differ The plot() produces the figure without problems for all versions of Splus (4.5 to 6.2) on Windows. Noticing that the plot() differs slightly between

Could someone identify a function that I might use to perform a components of variance analysis? In addition to the variance attributable to each factor, I would also like to obtain the SE of the variances. Thank you, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of

Dear everyone, I'm encountering an unknown error message when using gamm function: > fitoutput <- gamm(cvd~as.factor(dow)+pm10+s(time,bs="cr",k=15,fx=TRUE)+s(tmean,bs="cr",k=7,fx=TRUE) + ,correlation=corAR1(form=~1|city),family=poisson,random=list(city=~pm10),data=mimp) Maximum number of PQL iterations: 20 iteration 1 iteration 2 iteration 3 iteration 4

All, I am having trouble with a "read.table()" function that is inside of another function. But if I call the function by itself, it works fine. Moreover, if I run the script on a Mac OS X (with the default Mac OS X version of R installed, rev 2.8), it works fine. But it does not work if I run it on windows vista (also default Windows version of R, rev. 2.8). Again, both

Hi STATISTICA has a function called "Two-way joining" (see http://www.statsoft.com/TEXTBOOK/stcluan.html#twotwo) and the reference material states that this is based on the method as published by Hartigan (found this paper: http://www.jstor.org/pss/2284710 through wikipedia). What is the relationship (if any) between the "heatmap" function in R and this technique? Is there an

Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum

Hi, I have installed the necessary tools for making a R package under windows and am sure these tool have been correctly configured. I am very new to try writing a package, so the error may be very obvious for you. Forgive me if it is too easy. My package name is *stam*, and i put it under the folder "D:/StatSoft/R/MyPackage/". I have two folders,*R* and *man*. Besides, i also have

Hello all, here's a real-world example: I'm measuring a quantity (d) at five sites (site1 thru site5) on a silicon wafer. There is a clear site-dependence of the measured value. To find out if this is a measurement artifact I measured the wafer four times: twice in the normal position (posN), and twice rotated by 180 degrees (posR). My data looks like this (full, self-contained code at

Hi All I have data like this tom randy mike dan doug height 150 152 155 134 141 I am trying to create a line plot, with names on X-axis and height measure on Y. how can i get it through R. I could get several versions which are close (dotchart, bargraph), but not quite the same thing. I am looking for something like

Dear all, In the SASmixed package there is an example of an analysis of a split-plot experiment. The model is fm1Semi <- lme( resistance ~ ET * position, data = Semiconductor, random = ~ 1 | Grp) where Grp in the Semiconductor dataset is defined as ET*Wafer. Is it possible to specify the grouping directly some way, e.g. like fm1Semi <- lme( resistance ~ ET * position, data =

Hi all, I just wonder what singular convergence means. Thanks. Yen Lin Error in lme.formula(Data ~ 1, random = ~1 | Wafer/fie/loc, subset = Wafer == : singular convergence (7) [[alternative HTML version deleted]]