similar to: can not use plot.Predict {rms} reproduce figure 7.8 from Regression Modeling Strategies (http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf)

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 All: I tried to replicate a case study described by Prof. Harrell in Chapter 7 of his Regression Modeling Strategies book, but failed on using anova.Design to reproduce his table 7.1, Following is the code: rm(list=ls()) library(Hmisc) library(Design) getHdata(counties) counties$older <- counties$age6574 + counties$age75 label(counties$older) <- '% age >= 65, 1990'

I'm an R newbie and had a question about the read.xls function. I've heard that this is often not a reliable function to use for importing data. However, I have created numerous xls files which contain information about voter turnout and macroeconomic indicators in India. I'm writing a paper on the relationship between economic growth and voter turnout. This is the command I use:

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

Hi all, I am running a set of logistic regressions, where we want to use some weights, and I am not sure whether what I am doing is reasonable or not. The dependent variable is turnout in an election - i.e. survey respondents were asked whether or not they voted. The percentage of those who say they voted is much higher than the actual turnout, probably due both to non-response bias and social

For those that missed out joining the amazing turnout of ~70 people here in Vancouver for the mini-workshop I did on the 27th last month, I am making available the 30 slides I used for the presentation. The slides were used in conjunction with me demonstrating it via command line. Alot was learned by both attendees, and quite possibly even more so by myself while teaching the material. I created

Trying out an unfamiliar package, the natural thing is to use the examples given in the package's manual - hopefully, the writers of the package wouldn't include examples which didn't work! Recently, though, I've been getting 'unexpected$undefined' error messages when doing this, despite having copy/pasted the text from the manual (taking out hard breaks on the way).

Hello all, I am currently attempting to replicate data from a political science article that utilized a Markov chain transition model to predict voter turnout intention at time *t*; the data was separated into two different models based on whether prior intent was to vote or not to vote. The details don't really matter. Mostly I am curious how to run a Markov chain transition model in R,

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

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

Just a reminder. The community meeting is scheduled to happen in about 2.5 hours. Please add topics you want to discuss and any updates you have to the meeting notepad at [1]. ~kaushal [1]: https://bit.ly/gluster-community-meetings

Hey all! In the spirit of trying something new with the Community Meeting, this next one is changing a bit. I'm calling it 'Gluster Global Meetup' for lack of a better name (names welcomed) - and we're putting it on a video call. Same time as the community meeting, but a little different on the format. Here's a video call link for this that I'll add to the community

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