similar to: can nlme do the complex multilevel model?

I'm trying to sort a DATAFRAME by a column "ID" that contains alphanumeric data. Specifically,"ID" contains integers all preceeded by the character "g" as in: g1, g6, g3, g19, g100, g2, g39 I am using the following code: DATAFRAME=DATAFRAME[order(DATAFRAME1$ID),] and was hoping it would sort the dataframe by ID in the following manner g1, g2, g3, g6, g19,

Hi, I am new to R. I have a matrix that I have assigned to the object ?colon?. > colon<-read.table("c:\\alon.txt",header=T,row.names=1) attach(colon) names(colon) The dimenstions are 2000 62. Each of the 62 columns (titled norm1, norm2, norm3, etc) has 2000 different numbers (?continuous? values) within it. I have also assigned a name for each of the 2000 rows of the

Dear R Users, I have to read data from many excel spreadsheets, all which have some frustrating formatting (lots of titles, headers, etc.). I am trying to work directly from source data and the number of the spreadsheets I would have to go through make reformatting one by one a pain. I have found lots of ways to read excel files, but my question is whether there is a way to only read

Dear People at R help, I am trying to figure out the syntax for a three-level logistic model with a single random effect (intercept): Data Collected My data consist of three levels: level 1 is four setting for each student (setting nested within student), and each student is registered in one of 14 universities (students nested within university). More detailed: A. 2,479 students who have a

Dear Colleagues, I have a dataframe with variables: [1] "ID" "category" "a11" "a12" "a13" "a21" [7] "a22" "a23" "a31" "a32" "b11" "b12" [13] "b13" "b21"

Hi all Background: I am not a samba expert, not even close! I have a ancient samba 3 (Server role: ROLE_DOMAIN_PDC) and I intend to migrate all files to a samba 4 (Server role: ROLE_DOMAIN_MEMBER) Users will stay in S3 for now. Samba 4 joined samba 3 with no problems. I rsync'ed all files and its permissions (rsync -a ...). But... I cannot find a way that makes S4 sees S3 users and groups

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). What I write is the following library(locfit) data(ais)

Dear R-Helpers: I am using trying to use *ddply* to extract min and max of a particular column in a data.frame. I am using two different forms of the function: ## var_name_to_split is a string -- something like "var1" which is the name of a column in data.frame ddply( df, .(as.name(var_name_to_split)), function(x) c(min(x[ , 3] , max(x[ , 3]))) ## fails with an error - case 1 ddply(

In the past 24 hours multiple persons have contacted me regarding the use of elliptic curve cryptography in tinc 1.1 in light of the suspicion that the NSA might have weakened algorithms and/or elliptic curves published by NIST. The new protocol in tinc 1.1 (SPTPS) uses ECDH and ECDSA to do session key exchange and authentication, in such a way that it has the perfect forward secrecy (PFS)

In the past 24 hours multiple persons have contacted me regarding the use of elliptic curve cryptography in tinc 1.1 in light of the suspicion that the NSA might have weakened algorithms and/or elliptic curves published by NIST. The new protocol in tinc 1.1 (SPTPS) uses ECDH and ECDSA to do session key exchange and authentication, in such a way that it has the perfect forward secrecy (PFS)

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). My program is the following: library(locfit)

Dear R users, I'm using the "reldist" add-on package to calculate relative distribution in R as part of my research project. The subject is a general mental health score ranging from 0 to 12 (integer values only) with 0 indicating no mental health problem and positive values meaning some or sever mental health problem. When I run the programme to compare the scores of population

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

Hi! I'm pretty raw when working with the R models (linear or not). I'm wondering has anybody worked with the NLME library and dichotomous outcomes. I have a binary outcome variable that I woul like to model in a nested (multilevel) model. I started to fit a logistic model to a NLS function, but could not suceed. I know there are better ways to do it in R with either the LRM or GLM wih

Hi R-Help. I am working on a data set with a 3-level nested structure. I have individuals nested in households and multiple observations on each individual. I assume that the individuals inside a given household are correlated and that the individuals are correlated with themselves over time. The data is not balanced. I have computed a GLMM with logit link function and two random normal

Hello everyone, I am trying to regress applicants' performance in an assessment center (AC) on their gender (individual level) and the size of the AC (group level) with a multi-level model: model.0 <- lme(performance ~ ACsize + gender, random = ~1 | ACNumber, method = "ML", control = list(opt = "optim")) I have 1047 applicants in 118 ACs: >

Hi, I'm trying to perform a power simulation for a simple multilevel model, using the function glmmPQL in R version 2.8.1. I want to extract the p-value for the fixed-effects portion of the regression, but I'm having trouble doing that. I can extract the coefficients (summary(fit)$coeff), and the covariance matrix (summary(fit)$varFix), but I can't grab the p-value (or the

Hello, Have someone performed a bootstrap in a multiple-mediator model? I am trying to compute a bootstrap in a multiple and multilevel mediation. Up top now, I have developed bootstraps in random coeffient models, but I am very lost concerning the mediation. Could someone to provide me some ideas about syntax in R? Thank you very much in advance, Bea

Dear all, I posted this two years ago, getting no answers or suggestions - now I am trying again, hoping something new is available in R. I am interested in an application of linear multilevel model with unequal selection probabilities at both levels. Do you know if there is an R function for multilevel pseudo-maximum likelihood estimation? Or is it possible to obtain these estimates using

Hi R folks (Dr. Bates in particular), In August 2005, Dr. Bates mentioned that the documentation for lme4 "will be in the form of a book with the working title 'Multilevel Modeling in R'" and I'm just wondering if there is an estimated date of publication or if it's still a long way off. The Rnews article does a great job of introducing the package, but I'm