similar to: median and data frames

Hi R Users, I have been trying to work out how to rename column names using grep, basically I have generated these column names using tapply: [1] "NAME" "X1.1" "X2.1" "X3.1" "X4.1" "X5.1" "X6.1" "X7.1" "X8.1" [10] "X1.2" "X2.2" "X3.2" "X4.2"

Hello, I have a question about modelling via glm. I have a dataset (see dput) that looks like as if it where poisson distributed (actually I would appreciate that) but it isnt because mean unequals var. > mean (x) [1] 901.7827 > var (x) [1] 132439.3 Anyway, I tried to model it via poisson and quasipoisson. Actually, just to get an impression how glm works. But I dont know how to

I would like to preform a t.test to each of the measured variables (sand.silt etc.) with a mean and sd for each of the treatments (up or down), and out put this as a table.... I am having a hard time starting- maybe it is to close to lunch. Any suggestions would be greatly appreciated. Stephen Sefick x <- (structure(list(sample. = structure(c(1L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 2L, 3L,

First I have a matrix called stocks1: > class(stocks1) [1] "matrix" Here are the first 5 rows of the last 4 columns: > stocks1[1:5,2:5] [,1] [,2] [,3] [,4] [1,] 80.73 31.95 25.4 25.69 [2,] 83.66 31.95 27.12 25.2 [3,] 83.27 32.93 28.74 26.29 [4,] 83.9 34.07 29.77 26.6 [5,] 82.74 35.18 30.24 27.41 Now, why can't I convert this into a dataframe?

Hi R Helpers, I have been looking for an example of how to execute different dplyr mutate statements on the same dataframe in a single step. I show how to do what I want to do by going from df0 to df1 to df2 to df3 by applying a mutate statement to each dataframe in sequence, but I would like to know if there is a way to execute this in a single step; so simply go from df0 to df1 while executing

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

?s 22:50 de 17/10/2024, Sparks, John escreveu: > Hi R Helpers, > > I have been looking for an example of how to execute different dplyr mutate statements on the same dataframe in a single step. I show how to do what I want to do by going from df0 to df1 to df2 to df3 by applying a mutate statement to each dataframe in sequence, but I would like to know if there is a way to execute this

Dear everyone I am a bit of a computer imbecile and are having problems with R. I am using R in my research project to do chi-square tests on data imported from excel . However I have som missing data in one of my variables (columns) and I need R to "exclude" these and make chi-square test on the data that I have. I use a formula to make 2x2 tables which is: data <-

Hello- I have a dataset which basically looks like this: Location Sex Date Time Verbal Self harm Violence_objects Violence A 1 1-4-2007 1800 3 0 1 3 A 1 1-4-2007 1230 2 1 2 4 D 2 2-4-2007 1100 0

Hello, I have a pedigree file such this: FAMID ID FA ID MO ID SEX STATUS 1 1 0 0 2 0 1 2 3 1 2 2 1 4 3 1 1 2 1 5 3 1 1 0 1 6 3 1 1 0 1 7 3 1 2 2 1 8 3 1 1 0 1 9 3 1 1 0 1 10 3 1 2 0 1 11 3 1 1 0 1 3 0 0 1 0 2 12 13

Hi everyone, I am trying to generate a conditional dummy variable ?X" with the following rules set X=1 if Y is =1, two years prior to the NA. [0,0,NA]. For example, if the pattern for Y is 0,0,NA then the X variable is =0 for all the two years prior to the NA. If the pattern for Y is 0,1,NA or 1,0,NA then the X =1 . To be clear, if 1,1,NA then the X=1 that first specific year, it

Hello all, I'm sorry if my question seems basic. Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain the following relation with my variables : (Yes,No)~ ?0 + Age We note this this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . After that we calculated : model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) summary(model1)

Dear List I am trying to fit a multinomial model using the mlogit package. Attempting to load the data into mlogit presents the following error. MLOG<-mlogit.data(Mult3,shape="long",choice="CHOICE",alt.var="mode.ids",indivs = "set3",chid.var = "obs") Error in `row.names<-.data.frame`(`*tmp*`, value = c("1.1", "1.2",

I think the subject says it all. I want to make a simple lattice plot, using xyplot with the argument type=c("l","a"). The problem then is that in the resulting plot it is difficult/impossible to see which plot corresponds to the average and which to the individual profiles. I triedthings like extra arguments lwd=c(1,3) or col=c("blue","red") hoping

Hi, Sorry, but how did you bring it out? Thanks On Fri, Dec 28, 2012 at 8:48 AM, arun kirshna [via R] < ml-node+s789695n4654093h10@n4.nabble.com> wrote: > Hi, > bp.sub<- structure(list(CODEA = c(1L, 3L, 4L, 7L, 8L, 9L, 10L, 11L, 12L, > 13L, 14L, 16L, 17L), C45 = c(NA, 2L, 2L, 2L, 2L, 1L, NA, 1L, > 1L, 2L, 1L, 2L, 1L), ragek = c(3L, 3L, 3L, 4L, 4L, 3L, 3L, 3L, > 3L, 3L,

Hola a todos, A partir de los siguientes datos: d <- list(`1` = structure(list(ped = c(1L, 1L, 1L, 1L, 1L, 1L, 1L), id = 1:7, father = c(2L, 0L, 0L, 2L, 2L, 2L, 2L), mother = c(3L, 0L, 0L, 3L, 3L, 3L, 3L), sex = c(2L, 1L, 2L, 2L, 2L, 1L, 2L), affected = c(1L, 2L, 1L, 1L, 2L, 2L, 2L)), row.names = c("1", "2", "3", "4", "5",

Dear Lenny, You can do this by using Age as an offset factor. dataset$wAge <- dataset$Age * 1.02 glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data = dataset) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie &

Dear Thierry, Thanks a lot for this answer, I mean i want to obtain such model *Behavior1 = ?0+?1*Age* , the purpose is to obtain *?1*. I want to be sure that the odds value could be the ?1. Or how to calculate it ? Thanks again for your precious help. Lenny <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>

Dear all, I am facing some problem with how to fit a "Baseline category Logit model" with R. Basically I am considering famous "Alligator" data as discussed by Agresti. This data can also be found here: https://onlinecourses.science.psu.edu/stat504/node/174 (there is also an accompanying R file, however the underlying R code could not load the data properly!!!) Below are

Dear all, I was wondering if anyone could help solve a problem of a missing interaction effect!! I carried out a 2 x 2 factorial experiment to see if eggs from 2 different locations (Origin = 1 or 2) had different hatching success under 2 different incubation schedules (Treat = 1 or 2). Six eggs were taken from 10 females (random = Female) at each location and split between the treatments,