similar to: nested ANOVA with fixed and random variables missing data

Dear R Community, I am attempting to transpose a dataset from rows to columns but am stuck. I have tried using reshape() with little luck, possibly due to the categorical nature of the data. For example: id<-c(1,2,2,3,3,3) author<-c("j","k","k","l","l","l")

Hi All, I'm working with some SAS code to analyze an experiment set up as follows: 66 subjects (colonies) treated with a random treatment (1-8) and measured at three time points. The data structure looks like: input colony tmt y1 y2 y3; y=y1; date=*1*; output; y=y2; date=*2*; output; y=y3; date=*3*; output; datalines; 1

I have a local library which depends on the expm library. The expm library is loaded into my personal space and I have the environment variable R_LIBS_USER set appropriately. The command "library(expm)" works just fine from the command line, and in fact the package works if I do the source() and dyn.load() commands by hand. The following sequence works: tmt% R CMD build

Martin, I am aware of --vanilla; I use it myself for some testing. In this case R_LIBS_USER was set externally (part of my login) and does not involve any of the R scripts. That means it is inherited by any subprocess. For example: tmt1495% R --vanilla --no-environ R version 3.3.1 (2016-06-21) -- "Bug in Your Hair" Copyright (C) 2016 The R Foundation for Statistical Computing

THANKS so very much for your help (previous and future!). I have a two follow-up questions. 1) You say that dispersion = 1 by definition ....dispersion changes from 1 to 13.5 when I go from binomial to quasibinomial....does this suggest that I should use the binomial? i.e., is the dispersion factor more important that the 2) Is there a cutoff for too much overdispersion - mine seems to be

I have a local library with functions that interrogates an institution-specific web API, so is not of interest to anyone outside of Mayo. For some reason the R CMD INSTALL command fails. See below: Build the library, then install it. tmt-local2127% R CMD build dart * checking for file ?dart/DESCRIPTION? ... OK * preparing ?dart?: * checking DESCRIPTION meta-information ... OK * installing

A user asked me about this and I can't figure it out. tmt% R R Under development (unstable) (2018-04-09 r74565) -- "Unsuffered Consequences" Copyright (C) 2018 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) > library(survival) > data(cgd0) Warning message: In data(cgd0) : data set ?cgd0? not found ---- The data set is present and can be

This is likely yet another instance of round off error, but it caught me by surprise. tmt% R --vanilla (headers skipped, version 3.0.2 on Linux) > load('qtest.rda') > length(temp) [1] 3622 > max(temp) >= quantile(temp, .98) 98% FALSE I can send the file to anyone who would like to understand this more deeply. The top 3% of the vector is a single repeated value. Terry

I am getting failure of build and check, for an Rd file that has a long argument list. Guess diagnosis: a quoted string beyond a certain point in the argument list is fatal. Example: Use the function below, create an Rd file for it with prompt(). Move the .Rd file to the man directory (no need to edit it) and try building dart.control <- function(server=c("production",

Good afternoon Using R 2.9.2 on a machine running Windows XP I have a longitudinal data set, with data on schools and their test scores over a four year period. I have centered year, and run the following m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random = ~I(year-2007.5)|schoolnum, na.action = "na.omit") where

I have library in development with a function that works when called from the top level, but fails under R CMD check. The paricular line of failure is rsum <- rowSums(kmat>0) where kmat is a dsCMatrix object. I'm currently stumped and looking for some ideas. I've created a stripped down library "ktest" that has only 3 functions: pedigree.R to create a pedigree or

I have data on the proportion of clutches experiencing different fates (e.g., 4 different sources of mortality) for 5 months . I need to test 1) if the overall proportion of these different fates is different over the entire study and 2) to see if there are monthly differences within (and among) fate types. Thus, I am pretty sure this is an RM analysis -( I measure the same quadrats each month).

I would like to have your comments regarding: 1) drivers/rhino.c ------------------ The following patch addresses some problems in drivers/rhino.c. Or that is what I think. I don't use this hardware. The patch: 1. Eliminates some usefulness definitions. 2. It removes code that evaluate the time. I can't see how the code actually does useful work. 3. The

Hello Running R2.9.2 on Windows XP I am puzzled by the performance of LME in situations where there are missing data. As I understand it, one of the strengths of this sort of model is how well it deals with missing data, yet lme requires nonmissing data. Thus, m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random =

I'm puzzled by as.matrix. It appears to work differently for Surv objects. Here is a session from my computer: tmt% R --vanilla > library(survival) Loading required package: splines > ytest <- Surv(1:3, c(1,0,1)) > is.matrix(ytest) >[1] TRUE > attr(ytest, 'type') [1] "right" > attr(as.matrix(ytest), 'type') [1] "right" >

My on-screen plots with the latest build are acting strange. If the y label is longer than some small value it is not shown. Here is the script of a job. A pdf graph is fine. I use xubuntu as the windowing system. tmt-local1334% R --vanilla R Under development (unstable) (2017-08-31 r73172) -- "Unsuffered Consequences" Copyright (C) 2017 The R Foundation for Statistical Computing

Hello, I am trying to run a mixed effects nested ANOVA but none of my codes are giving me any meaningful results and I am not sure what I am doing wrong. I am a new user on R and would appreciate some help. The experimental design is that I have some frogs that have been exposed to three acoustic Treatments and I am measuring neural activity (egr), in 12 brain regions. Some frogs also called

Dear All, I sent already before a message concerning Levene's test in nested model, but I didn't get any answer. Optimistically I hope to get an answer this time. I also point a new question related to the whole model, because I haven't find any sure answer if I am analysing it in a suitable way or not. I really have tried to do my homework. I have response variable (y) and four

I have a debugging environment for the survival package, perhaps unique to me, but I find it works very well. To wit, a separate directory with copies of the source code but none of the package accuements of DESCRIPTION, NAMESPACE, etc. This separate space does NOT contain a copy of src/init.c Within this I use R --vanilla, attach my .RData file, survival.so file, and away we go. That is,

On Wed, 2017-02-08 at 15:51 -0600, Therneau, Terry M., Ph.D. wrote: > I have a local library which depends on the expm library.??The expm library is loaded into? > my personal space and I have the environment variable R_LIBS_USER set appropriately.??The? > command "library(expm)" works just fine from the command line, and in fact the package? > works if I do the source() and