similar to: Restricted cubic spline function ERROR?: glm(Y~rcs(x,5))

Dear list, I'm currently analyzing some count data using a hurdle model. I've used the rcspline.eval function in the Hmisc-library to contruct the spline terms for the regression model, and what I want in the end is the ability to compute coefficients and confidence intervals for different changes in the smooth function as well as plotting the smooth function along with the

Hi all, I have a vector of proportions (post_op_prw) such that >summary(amb$post_op_prw) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.0000 0.0000 0.0000 0.3985 0.9134 0.9962 1.0000 > summary(cut2(amb$post_op_prw,0.0001)) [0.0000,0.0001) [0.0001,0.9962] NA's 1904 1672 1

Hi, I am using the rcs() function in the Design library to model non-linearity that is not well characterized by an otherwise mechanistic function. I am able to make the model 'available' to others through the excellent nomogram() function and the set of tables that it can create. However, I would like to present the model in an 'expanded' format-- probably what rcspline.restate()

In the book, "Regression Modeling Strategies", Frank Harrell uses the function rcs() often. The current version or R and Hmisc library don't appear to have this function. What is an appropriate substitute? Thank You -- Noah Silverman UCLA Department of Statistics 8208 Math Sciences Building Los Angeles, CA 90095 [[alternative HTML version deleted]]

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

Dear Thomas, I want to use evaluate effect of Age using restricted cubic form in the FGR function as Fgr.crr <- FGR(Hist(time, event) ~ rcs(Age_years), data=dat) It provides error. " Error in parse(text = termtext, keep.source = FALSE): .... 1: response ~ rcs(Age_years Do I need to change any of the R code? Regards Amalraj Raja The University of Aberdeen is a charity

Hello,   does anyone have an example on how to use restricted cubic splines function rcs within survfit.cph, if cph (Cox Proportional Hazard Regression) was done with restricted cubic splines (which I made to work)? Thank you. > [[alternative HTML version deleted]]

Dear Dr ; I am a PhD student at Epidemiology department of National University of Singapore. I used R command (rcspline.plot) for plotting restricted cubic spline ??? the model is based on Cox. I managed to get a plot without adjustment for other covariates, but I have a problem regarding to adjusting the confounders. I applied below command to generate the matrix for

Dear R list, From the lrm() binary logistic model we derived the G2 value or the likelihood-ratio chi-squared statistic given as L.R. model, in the output of the lrm(). How can this value be penalized for non-linearity (we used splines in the lrm function)? lrm.iRVI <- lrm(arson ~ rcs(iRVI,5), penalty=list(simple=10,nonlinear=100,nonlinear.interaction=4)) This didn’t work

Hi, I'm trying to get the 'xts' library from CRAN packaged for Fedora 12, and one of its dependencies is 'Hmisc'. I have created a spec file for that using R2spec, but building it fails with something in building the manual pages: Warning: ./man/escapeRegex.Rd:22: unknown macro '\backslash' [similar warnings snipped] Warning: newline within quoted string at

Dear r-list, When I try to plot the following 3D lrm fit I obtain only arrows with labels on the three axes of the figure (without values). fit <- lrm(y ~ rcs(x1,knots)+rcs(x2,knots), tol=1e-14,X=T,Y=T) dd <- datadist(x1,x2);options(datadist='dd'); par(mfrow=c(1,1)) plot(fit,x1=NA, x2=NA, theta=50,phi=25) How can I add values to the axes of this plot? (axes with the

Dear, When fitting the following model knots <- 5 lrm.NDWI <- lrm(m.arson ~ rcs(NDWI,knots) I obtain the following result: Logistic Regression Model lrm(formula = m.arson ~ rcs(NDWI, knots)) Frequencies of Responses 0 1 666 35 Obs Max Deriv Model L.R. d.f. P C Dxy Gamma Tau-a R2 Brier 701 5e-07 34.49

http://r.789695.n4.nabble.com/file/n3058505/file.csv file.csv Hi, Rusers I have a problem in making a rcspline.plot with a Hmisc package. My data is in the upload attachment. My programme as follows: library(Hmisc) A<-read.csv("file.csv",header=TRUE) attach(A)

Dear R-list, Is there a function or technique by which the probability (or log odds) range of a logistic model (fit <- lrm(Y~X)) can be derived? The aim is to obtain min & max of the estimated probabilities of Y. Could summary.Design() be used for that or is there another method/trick? Thanks, Jan _______________________________________________________________________ ir. Jan

Apologies if this is this too obscure for R-help. In package splines, ns(x,,knots,intercept=TRUE) produces an n by K+2 matrix N, the values of K+2 basis functions for the natural splines with K (internal) knots, evaluated at x. It does this by first generating an n by K+4 matrix B of unconstrained splines, then postmultiplying B by H, a K+4 by K+2 representation of the nullspace of C (2 by K+4),

Dear R-list, *When comparing two logistic regression models with the anova CHi test, I obtain the following error: (there are no NA's in the time series). How can this be solved such that I can compare two models on the same dataset were different explanatory variables are used? l.KBDI <- glm(zna.arson2 ~ zna.KBDI,family = binomial) l.NDWI <- glm(zna.arson2 ~ zna.NDWI,family

You wrote: "It may be best to either write to the package maintainer (me, as you did) or post to the group but not both." This is just a note that I disagree wrt my own packages: I go on vacation or trips, or have other projects so won't always answer Other folks on the list often have good ideas that I'd miss My preferred standard is "ask the list, with a copy

Hi, When running z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image') Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)), zlab='Probability') And after pointing the cursor to the plot() screen in R, I obtain the following message: Using function "locator(2)" to place opposite corners of image.legend Error in

I have a question about the basis functions of cubic regression spline in mgcv. Are there some ways I can get the exact forms of the basis functions and the penalty matrix that are used in mgcv? Thanks in advance! Yan [[alternative HTML version deleted]]

Hi Users, I want to fit the maximums of a data series with a cubic spline. How do I go about this in R. I failed to figure out how I can use the mgcv library to do this. Thanks ---------------------------- ZABLONE