similar to: scope of data in groupedData

Dear Group: I have been trying to write an R function within which the function groupedData() would be used. The following is a sample program: ####################### sid<-rep(1:6,times=2) time<-c(1:12) trt<-rep(letters[1:3],times=4) tem<-data.frame(sid,time,trt) test1.fun<- function(dat=dat) { groupedData(time ~ trt|sid, data=dat) } test1.fun(dat=tem)

Greetings, I have a groupedData (nmGroupedData) object created with the following syntax: Soil <- groupedData( ksat ~ conc | soil_id/sar/rep, data=soil.data, labels=list(x='Solution Concentration', y='Saturated Hydraulic Conductivity'), units=list(x='(cmol_c)', y='(cm/s)') ) the original data represents longitudinal observations in the form of:

Dear all, I'm using the nlme package. I would like to introduce the plot of my groupedData object in my latex report using Sweave but it doesn't work. I have no error message in R (Sweave(my.file_Rnw)) and the plot is generated in R, but when I want to see the pdf (I'm using TexnicCenter) of my report, there is an error message and no pdf file is generated. It seems that the plot

Windows Vista R 2.10.1 Does the following use of groupedData and lme produce an analysis with both random intercept and slope, or only random slope? zz<-groupedData(y~time | Subject,data=data.frame(data), labels = list( x = "Time", y = "y" ), units = list( x = "(yr)", y = "(mm)") ) plot(zz)

help.search("groupedData") says that it's part of the lme4 package, but it appears not to be there (details below). Is this because lme4 is new and (perhaps) still under development? > update.packages() trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 19113 bytes opened URL downloaded 18Kb >

Dear R-help, I am trying to create groupedData objects using the nlme library. I'm missing something basic, I know: Here is the first example in ch.1 of Pinheiro & Bates (2000): library(nlme) x2=Rail$travel;x1=Rail$Rail;eg1=data.frame(x1,x2);eg1gd=Rail print(eg1gd) x11();print(plot(eg1gd)) femodel=lm(x2~x1-1,data=eg1gd) print(femodel$coefficients) Result: x12 x15 x11

Dear R Help, I am having difficulty using Variogram within GLS to examine spatial structure of nested data. My data frame consists of ecological measurements of a forest, in which three landscape positions ("landposi") are compared. Each landscape position is replicated five times ("replicat"), and the environment is measured ("canopy", "litdepth", etc.)

Dear John You are only allowed to have the primary covariate on the left hand side of the vertical bar. Other covariates go in inner or outer. Michael On 22/03/2018 12:59, Sorkin, John wrote: > Windows 10 64-bit, R-Studio, R version 3.4.3 > > > Several questions relating to groupedData: > > (1) I am trying to create a groupedData object that can be used to run an analysis

I'm using groupedData from nlme. I set up a groupedData data.frame with outer=~group1. When I try to plot with outer=TRUE, I get "subscript out of bounds." This happens most of the time. When it works, I get spaghetti-type plots for comparing groups. But I don't understand why it doesn't usually work. > longa.mod.1.gd <- groupedData(mod1.logit~time|

Windows 10 64-bit, R-Studio, R version 3.4.3 Several questions relating to groupedData: (1) I am trying to create a groupedData object that can be used to run an analysis that I have been able to urn using lmer. When I include the interaction terms in the groupedData opbject I get an error message stating that + is not meaningful for factors. How do I include factors in my model? See code and

Hello, I'm trying to use the groupedData function and R is giving me the message: Error: can not find function "groupedData" The code is coming from a textbook so I think it should be correct: pigs<-data.frame(cbind(pig.time,pig.id,pig.wt)) pig.growth<-groupedData(pig.wt~pig.time|pig.id,data=pigs) I have added the package "nlme" and to confirm that it was installed

Hi,   I have an original data frame with 8 columns of variables, which are stored in 'data1' frame.   data1 <- read.csv("E:\\PHD GLASGOW UNIVERSITY\\Data\\R\\Colin\\Cailness21.csv") attach(data1) names(data1)   [1] "Date"       "d"          "m"          "y"          "Time"      [6] "Depth"      "Temp"      

Hello I am trying to fit a REML to some soil mineral data which has been collected over the time period 1999 - 2004. I want to know if the 19 different treatments imposed, differ in terms of their soil mineral content. A tree model of the data has shown differences between the treatments can be attributed to the Magnesium, Potassium and organic matter content of the soil, with Magnesium being the

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >

Dear Experts, I need to include the repeated structure in our data set object, recall.sums.df, before using gls function. Thus I used groupedData. But I encountered error messages which may mean '*' is not not meaningful factor. Please let me know what I have to do. Thanks, Jeong > recall.sums.df[0:10, ] recall.values recall.ind subj replication hemi region group 1 17.515

Dear all, I tried to create a groupedData object, where the grouping factor is not ordered. Here ist the code: library(nlme) test<-groupedData(conc~Time|Subject,order.groups=F,data=as.data.frame(Theoph)) > getGroups(test) Levels: 6 < 7 < 8 < 11 < 3 < 2 < 4 < 9 < 12 < 10 < 1 < 5 I still get an ordered factor. As always thanks for your help peter

Dear R-users, I'm currently having trouble with the implementation of a groupedData object in the lme() function. Executing the following function > applyScalingSimp <- function(input.population) > { > ## GA is a time value > varInOrder <- c("GA","weight","grouping","sex") > modelVar <-

Hi, Does anyone know how to make the color of the lines all black when plotting groupedData with an outer factor: For example, library(nlme) plot(Dialyzer, outer=~QB, key=F) This generated colored curves in R.2.4.1. How to make all the curves black ? (or how to alter the color (type) of lines for the nlme groupedData plotting function in general?) Thanks Qiong

I am trying to create a plot similar to Figure 3.2 in Bates and Pinheiro. I have repeated measurements on about 80 subjects from 2 treatment groups. I would like to have the panels for the two treatment groups in separate groups and within those groups have the panels ordered on maximum value (as is the default). I am ok with getting plots similar to Figs 3.1 and 3.2, but can't see how to

Dear All, I would be grateful if you can tell how can I suppress the legend (automatically created) when I plot a groupedData. suppose that I have data farme df_0 which contains the following columns: ID represents the clusters, t represents time of observation, Y: the variable of interest and X a binary covariate. Then: df_1 <- groupedData(Y ~ t | ID) plot(df_1,