search for: inclx

...;t get it to work. I say m1 <- matrix(1:20+rnorm(20),5,) # four correlated variables colnames(m1) <- paste("R",1:4,sep="") m1[c(2,19)] <- NA # simulate some missing data library(Hmisc) transcan(m1,data=m1) and I get Error in rcspline.eval(y, nk = nk, inclx = TRUE) : fewer than 6 non-missing observations with knots omitted I've tried a few other things, but I think it is time to ask for help. The specific problem is a real one. Our graduate admissions committee (4 members) rates applications, and we average the ratings to get an overall...

Dear all, As I am new to the R community - although eager to advance- I would like to pose a question to the community. I have an SPSS file which I have imported it in R (with the read.spss command) which conists of scale (continuous) variable "adiponectin" and the corresponding categorical value "death" (0=No, 1=Yes). In all there are 60 observations (among which

...e confidence interval at the values of the x-variable. An example using the "zero"-part of the hurdle model: library(Hmisc) library(pscl) # Simulate some data set.seed(1) y<-c(rep(0,50),rnbinom(50,0.9,0.2)) x<-sin(y)+rnorm(100) # Set up the spline terms ssp<-rcspline.eval(x,inclx=T) # Fit the model and construct the smooth function f<-hurdle(y~ssp) knots<-attr(ssp,"knots") coef<-f$coefficients$zero w<-rcspline.restate(knots,coef) fun<-eval(attr(w,"function")) The coefficient for a change in x from -0.1 to 0.1 is fun(0.1)-fun(-0.1). My q...

...al(input.population[,modelVar["GA"]], > > knots=quantile(input.population[,modelVar["GA"]], > > probs=qVec<-c(0.05,0.275,0.5,0.725,0.95),na.rm=TRUE), > inclx=TRUE) > > colnames(GASpline) <- > paste("GA",head(seq_along(qVec),n=-1),sep="") > input.population <- cbind(input.population,GASpline) > > lmeFormula <- as.formula(paste("VARI1", "~", > modelVar["se...