similar to: groupedData Error Using outer=TRUE

Hello everyone, I am ploting a groupeddata object with formula: formula(mydatausegroup) BF ~ HO | ID/Infar/Day Using this command: plot(na.omit(mydatausegroup), displayLevel=2,layout=c(10,2),aspect=2) This trellis plot does almost what I want and produces a 10x2 trellis plot, each panel is labeled as ID/Infar where infarct is either 1 or 0. And in each panel, it plots BF vs HO for each Day.

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

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 am having trouble specifying a suitable nlme model. My data structure is described by gd <- groupedData(ppath ~ lcut | exp, outer = ~ bait, inner = ~ weight, data = d) i.e. the response (ppath) of several subjects (sub) was measured at levels of a continuous variable (lcut). Subjects were given either of one level of a factor (bait), and all subjects were measured at two levels

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 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)

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

Given a data frame consisting of a pointID and 12 pairs of (lat, long) variables, with names latA, longA, latB, longB, ... latL, longL, I want to reshape it into a data frame with the structure point source lat long 1 A ... ... 1 B ... ... I've looked at reshape and plyr, but can't figure out how to do this. Details of my data frame are below

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. >

I'm trying to write a function that has a dataframe as an argument. Within the function, I call groupedData to create a grouped-data object from the dataframe argument. However, the groupedData function doesn't seem to see the data. I'm guessing it's getting the argument name rather than its value, but I'm not positive. My system: R 1.3.1 on WinNT 4.0 (Pentium II), nlme

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

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)

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,

Dear Experts, May be the problem is still solved, however I tried to find the answer in the archives: I use: > R.version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 7.1 year 2003 month 06 day 16