similar to: R: anova.Design

Dear R-users: I am trying to use the following code to reproduce the figures on page 140 of Prof. Frank Harrell's book 'Regression Modeling Strategies': rm(list=ls()) options(width=128) library(Hmisc) library(Design) getHdata(counties) counties$older <- counties$age6574 + counties$age75 label(counties$older) <- '% age >= 65, 1990' counties$pdensity <-

Dear R-users, I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the handouts *Regression Modeling Strategies* ( http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the following code. Could any one help me figure out how to solve this? setwd('C:/Rharrell') require(rms) load('data/counties.sav') older <- counties$age6574 + counties$age75

You report an error message: > plot(zph.revasFit[1]) Error in plot.window(xlim, ylim, log, asp, ...) : need finite 'ylim' values I have never seen this error before, and I cannot guess what causes it. You need to provide more information, and likely a small data set that produces the problem. Perhaps you have an x variable that is a constant? Terry Therneau

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Dear All, I've installed Postfix 2.7.0 and Dovecot 1.2.9 on Ubuntu 10.04. I want to use Dovecot SASL with Postfix and did the following configuration. main.cf smtpd_sasl_auth_enable = yes smtpd_sasl_type = dovecot smtpd_sasl_path = private/dovecot-auth smtpd_sasl_authenticated_header = yes smtpd_sasl_security_options = noanonymous smtpd_sasl_local_domain = $myhostname

I was glad to see the new rpart.plot package by Stephen Milborrow. I was however a bit concerned that Stephen distributed a dataset I created, and renamed the dataset (from titanic3 to ptitanic) in the process [with some justification, as some variables were omitted]. Fortunately Stephen included the script he used to download the dataset from our web site, and gave full credit to us. What

Hi, Again I'm doing logistic regression using lrm from Harrell's Design package, but on wide matrices (28 observations, 1891 variables) so L2 penalisation is used. I get the following error, although I've tried different penalties and different tolerances. The X matrix is scaled and centred. > library(Design) >

Dear R-users: I can not reproduce figure 4 of *Statistical Tables and Plots using S and LATEX* by Prof. Frank Harrell with the following code: rm(list=ls()) library(Hmisc) getHdata(pbc) attach(pbc) age.groups <- cut2(age, c(45,60)) g <- function(y) apply(y, 2, quantile, c(.25,.5,.75)) y <- with(pbc, cbind(Chol=chol,Bili=bili)) # You can give new column names that are not legal S names

Hi R-users,   I have this code here: library(numDeriv)   fprime <- function(z) { alp  <- 2.0165;   rho  <- 0.868;   # simplified expressions   a      <- alp-0.5   c1     <- sqrt(pi)/(gamma(alp)*(1-rho)^alp)   c2     <- sqrt(rho)/(1-rho)   t1     <- exp(-z/(1-rho))   t2     <- (z/(2*c2))^a   bes1   <- besselI(z*c2,a)   t1bes1 <- t1*bes1   c1*t1bes1*t2 }   ## Newton

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the

When I try to the code from library(survival) of library(ISwR), the following code survfit(Surv(days,status==1)) that could produce Kaplan-Meier estimates shows the following error "Error in survfit(Surv(days, status == 1)) : Survfit requires a formula or a coxph fit as the first argument" How it can be done in R.2.10 -- View this message in context:

hi, i have 2 tables (counties and towns). counties has_many towns and towns belong_to counties. now my question: i thought i would need to do is say @counties = Counties.find(:all). should that not return to me all counties in the counties table WITH all towns associated with each county? in my view i was getting error when doing this if(counties.has_towns?) saying undefined has_towns

Dear Rers, is there a way to color counties on a full US map based on a criterion one establishes (i.e., all counties I assign the same number should be the same color)? I explored a bit and looks like the package "maps" might be of help. library(maps) One could get a map of the US: map('usa') One could get countries within a US state: map('county', 'iowa', fill

Quick question. Say I have a geographical database with counties and zip codes where counties have and belong to many zip codes. zip_codes (id, zip_code) counties (id, name) When I create the association table, the Rails way says to do the following: counties_zip_codes (county_id, zip_code_id). However, given that zip_codes.zip_code is itself a candidate key, I would much prefer to do the

Is there an R equivalent to SAS's proc gremove? You would use this procedure to combine the units on an existing map, for example to build a map of Metropolitan Statistical Areas (MSAs) from the [US] counties dataset where the internal boundries surround the MSAs (which are groups of counties) rather than the individual counties. I can imagine the mechanism would be to find and erase the

Dear R'ers, I am wondering what is the smallest geographicterritorial unit available for formatting in Canada. Provinces? I know that in the US it is the county so that I can color US counties any way I want, for example: ### Example for coloring US counties ### Creating an ARTIFICIAL criterion for coloring US counties: library(maps) allcounties<-data.frame(county=map('county',

I am using "maps". I am running the following code to get this list of all the counties: map('county', plot=FALSE)$names In the output, all counties have first the state listed and then, after a comma, the name of the county. However, county # 2395 (State = south dakota) has no county name. Anyone knows what this county is? Thank you! -- Dimitri Liakhovitski

Hi, I have a question which is a little off-topic but then again, it should stay in the boundaries of what can be done with available R functions. Has anyone pointers to tutorials or the like where one can get inspiration on how to visualize some "spatial" statistics? I want to analyze different statistics of 60 counties in a country. I have a shape file for those counties thus I can

Hi, Can anyone help me with either of these: 1) Map of the UK counties that I could use in R? 2) How could I use an existing map for example, a map from here http://www.itraveluk.co.uk/maps/england.html - in R. I need to use a UK map to plot locations on it by lat & long. Would appreciate help on any of these. Thanks, Raoul -- View this message in context:

Hi, Four tables: users, user_counties, uk_counties and us_counties. Each user has many counties, and each county has many users, so I decided to make user_counties a polymorph, so it can have counties from different countries (each country requires a completely different set of tables with a completely different set of properties, that''s why there''s one table for uk_counties and