similar to: reorder [stats] and reorder.factor [lattice]

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function

Kia ora list members: I'm having a little difficulty getting the correct standard errors from a glm.object (R 1.9.0 under Windows XP 5.1). predict() will gives standard errors of the predicted values, but I am wanting the standard errors of the mean. To clarify: Assume I have a 4x3x2 factorial with 2 complete replications (i.e. 48 observations, I've appended a dummy set of data at the

Hello, R experts, I have a list called dataHP which has 30 elements (m1, m2, ..., m30). Each element is a 7x6 matrix holding yield data from two factors experimental design, with treatment in column, position in row. For instance, the element 20 is: dataHP[[20]] col1 col2 col3 trt1 trt2 trt3 [1,] 22.0 20.3 29.7 63.3 78.5 76.4 [2,]

> library(MASS) > attach(bacteria) > table(y) y n y 43 177 > y<-1*(y=="y") > table(y,trt) trt y placebo drug drug+ 0 12 18 13 1 84 44 49 > library(lme4) > model1<-lmer(y~trt+(week|ID),family=binomial,method="PQL") Error in match.arg(method, c("Laplace", "AGQ")) : 'arg' should be one of

Hello,   Could you please help me in the following question: I have 16 persons 6 take 0.5 mg, 6 take 0.75 mg and 4 take placebo! Can I use the ANCOVA and t-test in this case? Is it possible in R?   Thank you in advance, Samuel [[alternative HTML version deleted]]

Hi, Searching for functions that would order strings that mix characters and numbers in a "natural" way (ie, "a1 a2 a10" instead of "a1 a10 a2"), I found the mixedsort and mixedorder from the gtools package. Problems: 1- mixedorder does not work in a "do.call(mixedorder, mydataframe)" call like the order function does 2- gtools has not been updated in 2.5

??? > y <- sort( c("a1","a2","a10","a12","a100")) > y [1] "a1" "a10" "a100" "a12" "a2" > mixedsort(y) [1] "a1" "a2" "a10" "a12" "a100" **Please read the docs!** They say that mixedsort() and mixedorder() both take a **single

Dear all, my aim is to estimate the efficacy over time of a treatment for headache prevention. Data consist of long sequences of repeated binary outcomes (1 if the subject has at least 1 episode of headache , 0 otherwise) on subjects randomized to placebo or treatment. I have fit a logistic regression model with Huber-White cluster sandwich covariance estimator. I have put in the model the

x <- c( "a1", "a10", "a2" ) y <- c( "b10", "b2", "a12", "ca1" ) DF <- expand.grid( x = x, y = y ) # randomize set.seed( 42 ) DF <- DF[ sample( nrow( DF ) ), ] # missing from gtools mixedrank <- function( x ) { seq.int( length( x ) )[ gtools::mixedorder(x) ] } o <- do.call( order, lapply( DF, mixedrank ) )

I have an outlier that I would still like to display, but would prefer to shorten the axis. For example, display 0% - 40%, and 90% - 100%. Is this possible? I am using an xyplot. Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

Hello List, I'm trying to do a paired t-test, and I'm wondering if it's consistent with equations. I have a dataset that has a response and two treatments (here's an example): ID trt order resp 17 1 0 1 0.0037513592 18 2 0 1 0.0118723051 19 4 0 1 0.0002610251 20 5 0 1 -0.0077951450 21 6 0 1 0.0022339952 22 7 0 2

In http://tolstoy.newcastle.edu.au/R/e2/help/06/10/3064.html a method was given for converting a frequency table to an expanded data frame representing each observation as a set of factors. A slightly modified version was later included in the NCStats package, only on http://rforge.net/ (and it has too many dependencies to be useful). I've tried to make it more general, allowing an input

It would be nifty to incorporate this into R or into an R package: http://sourcefrog.net/projects/natsort/

I am trying to reorder a factor data type so that when I plot stats associated with the factor, the ordering makes sense. For instance, if I have a factor entered as follows ... A = as.factor(c("1", "10", "3", "3", "10", "10")) levels(A) ... the ordering does not really make sense (assuming I want the factor ordered by integer

split any mixed columns into letter and number columns and then order can be used on that: DF <- data.frame(x = c("a10", "a2", "a1")) o <- do.call("order", transform(DF, let = gsub("\\d", "", x), no = as.numeric(gsub("\\D", "", x)),

Thanks for that answer. I was not aware of gtools::mixedsort <https://www.rdocumentation.org/packages/gtools/versions/3.5.0/topics/mixedsort> function. Jean On Thu, Jun 29, 2017 at 2:47 PM, Henrik Bengtsson < henrik.bengtsson at gmail.com> wrote: > You can use: > > > files <- list.files(path = "folder01") > > files <- gtools::mixedsort(files) >

1- mixedorder does not work in a "do.call(mixedorder, mydataframe)" call like the order function does This is tangential, but do.call(order, mydataframe) is not safe to use in a general purpose function either - you need to remove the names from the second argument: > d <- data.frame(method=c("New","New","Old","Old","Old"),

Hi R users, I have a question about opening the txt files and putting them into a matrix. The txt files are in the folder01, while they have the name file.1.txt, file.2.txt, file.3.txt, etc. There are about 200 such text files. Each txt file contains one value inside. When I tried to use the code below, I found that the txt files are not in order, from 1, 2, 3, to 200. Rather, they are in the

You can use: > files <- list.files(path = "folder01") > files <- gtools::mixedsort(files) to order the files in a "human-friendly" order rather than lexicographic order (which sort() provides). FYI 1; it's preferred to use file.path("folder01", list[i]) rather than paste('folder01',lists[i],sep='/'). FYI 2; if you use

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence intervals). Let me give sample data # Data