similar to: Help using tapply with multiple variables

I am trying to read a SAS dataset into R that is in a .SD2 format, which is the Version 6 standard format from SAS. I see the routines that read the SAS XPORT format (foreign, Hmisc), but is there any way to read this one? Any help would be greatly appreciated. Corey Sparks Corey Sparks Assistant Professor Department of Demography and Organization Studies University of Texas-San Antonio One UTSA

I am trying to develop scatter plots using library(car). However, the output I am getting shows the axis (x and y) in scientific notation. I want to have the axis represented by regular integers (for eg. the X axis i want the upper bound to show as 40,000,000 instead of 4.0e+07). Scanning the r-help archives did not get me the answer. I have uploaded my data here: http://bit.ly/olgMLt

Dear list, I am trying to use gregexpr to see if entries in a dataframe have either of two possible values for a string. here's an example text<-c("fat", "rat", "cat", "dog", "log", "fish") If I just wanted to find if any one of the elements in text match the pattern "at" I would do gregexpr("\\at", text)

Dear list, I am fitting a logistic multi-level regression model and need to test the difference between the ordinary logistic regression from a glm() fit and the mixed effects fit from glmer(), basically I want to do a likelihood ratio test between the two fits. The data are like this: My outcome is a (1,0) for health status, I have several (1,0) dummy variables RURAL, SMOKE, DRINK, EMPLOYED,

Hello, I am running R 2.6.1 on windows xp I am trying to fit a cox proportional hazard model with a shared Gaussian frailty term using coxme My model is specified as: nofit1<-coxme(Surv(Age,cen1new)~ Sex+bo2+bo3,random=~1|isl,data=mydat) With x1-x3 being dummy variables, and isl being the community level variable with 4 levels. Does anyone know if there is a way to get the standard error

Dear R Users, I'm working on a problem where I have a multivariate response vector of counts and a continuous predictor. I've thought about doing this the same way you would do a Multvariate regression model with normally distributed data, but since these data are counts, they are probably better modeled with a Poisson distribution. For example y1<-rpois(100,3.5) y2<-rpois(100,1.5)

Hi R users, I'm using the survey package to calculate summary statistics for a large health survey (the Demographic and Health Survey for Honduras, 2006), and when I try to calculate the variances for several variables, I get negative numbers. I thought it may be my data, so I ran the example on the help page: data(api) ## one-stage cluster sample dclus1<-svydesign(id=~dnum, weights=~pw,

> Dear list, > > I have some data on a geneaology, here is a subset: > warmerge[1:11,c(1,6,25)] > Warrior SibID birth.year > 1100 3793 2013 1926 > 4 2013 2024 1934 > 1094 3769 2024 1918 > 632 2747 2037 1928 > 176 2083 2039 1944 > 187 2085 2039 1949 > 192 2086 2039 NA > 495

Hi all, I have a following problem: - Remus network buffering doesn''t work. It seems to be because of no vif is reported by the function server.xend.domain on line 29 of /usr/local/lib/python2.7/dist-packages/xen/remus/vm.py (seen using pdb) : 27 if domid: 28 try: 29 self.dominfo = server.xend.domain(domid, ''all'') >

Hello, I''ve recently setup a Linux Dom0 with a 3.0.17 kernel and Xen 4.1.2, and since the 3.x series doesn''t have blktap support I''m using qdisk to attach raw images. I''ve been playing with small images, something like 1GB, and everything seemed fine, speed was not fantastic but it was ok. Today I''ve set up a bigger machine, with a 20GB raw hdd and the

Dear R Help, I read through the archives pretty extensively before sending this email, as it seemed there were several threads on using predict with GLM. However, while my issue is similar to previous posts (cannot get it to predict using new data), none of the suggested fixes are working. The important bits of my code: set.seed(644) n0=200 #number of observations

Hello all, I would like to get parameter estimates for different models. For one of them I give the code in example. I am estimating the parameters (i,j and k) with the nls function, which sees the error distribution as normal, I would however like to do the same as nls with the assumption that the errors are poisson distributed. Is there a way to do this with R? Are there packages designed

Hi all, I have some problems with the mle2 function > RogersIIbinom <- function(N0,attackR3_B,Th3_B) {N0-lambertW(attackR3_B*Th3_B*N0*exp(-attackR3_B*(24-Th3_B*N0)))/(attackR3_B*Th3_B)} > RogersII_B <- mle2(FR~dbinom(size=N0,prob=RogersIIbinom(N0,attackR3_B,Th3_B)/N0),start=list(attackR3_B=1.5,Th3_B=0.04),method="Nelder-Mead",data=dat) Error in dbinom(x, size, prob, log)

Hi, I am new in R and stumbled on a problem my (more experienced) friends can not help with with. Why isnt this code working? The function is working, also with the loop and the graph appears, only when I build another loop around it (for different values of p) , R stays in a loop? Can't it take more then 2 loops in one program? powerb<-function(x,sp2,a,b,b1,m) {

Hi all, I've been working on a backend of our architecture and noticed llvm performs following combining although one of operands is FrameIndex. Combining: t114: i64 = add FrameIndex:i64<0>, Constant:i64<56> Creating new node: t121: i64 = or FrameIndex:i64<0>, Constant:i64<56> ... into: t121: i64 = or FrameIndex:i64<0>, Constant:i64<56> This

I am trying to define a general R function that has a function as the output that depends on the user's input arguments (this may make more sense by looking at the toy example below). My real use for this type of code is to allow a user to choose from many parameterizations of the same general model. My "issue" is that when I compile a package with this type of code in it I get a

Dear R users, I am interested in taking the columns from multiple dataframes, the problem is that the different dataframes have different combinations of the same variable names, here's a simple example: a<-rep(1:10) b<-rep(1:10) c<-rep(21:30) d<-rep(31:40) dat.a<-data.frame(a,b,c,d) names(dat.a)<-c("a", "b", "c", "d")

Hi all, When I try to estimate the functional response of the Rogers type I equation (for the mle2 you need the package bbmle): > RogersIbinom <- function(N0,attackR2_B,u_B) {attackR2_B+u_B*N0} > RogersI_B <- mle2(FR~dbinom(size=N0,prob=RogersIbinom(N0,attackR2_B,u_B)/N0),start=list(attackR2_B=4.5,u_B=0.16),method="Nelder-Mead",data=data5) I get following error message

Hi All, Apologies for the simplicity of my question, but I would be grateful for any advice. Thanks I'm trying to put the output from a for loop into a data frame, however I have not been successful. The steps I have taken are: *R-code:* >for (k in 1:(nt-1-n0) ){ > n<- n0-1+k > lam=n/nt > Q=x[n] > output1<-data.frame(cbind(k,n,lam,Q)) > output1 > }

I've got a covariance matrix that I'd like to index using the dimnames: > vcov1 n0 x0 s n1 n2 n0 82.43824759 1.839505e-02 -4.975196e-01 2.882394e+03 -2.615986e-01 x0 0.01839505 6.134010e-03 -7.695922e-04 -6.373946e+01 6.086321e-03 s -0.49751964 -7.695922e-04 9.638943e-03 3.406594e+02 -3.173671e-02 n1 2882.39407745