similar to: plot CI and mortality rate

Dear R Group: Based on the following data, how to do a great Spider (Radar) Plot? Any advice is greatly appreciated. HospID Rate Age Charlson NIHSS 1 0.2 49 3.5 0 2 0.1 48 1.8 12 3 0.4 56 2.1 5 4 0.3 77 0 7 5 0.2 67 6.5 3 6 0.1 62 4.8 4.6 7 0.1 64 12 5.2 8 0.3 61 3 2.8 9 0.15 69 4.5 1.9 10 0.22 80 0 6.7 11 0.34 61 6 4.2 12 0.18 63 3 6.1 13 0.09 64 8 15 12 0 56 10 11 15 0.1 70 11 7 16

Dear R Group: How to import multiple csv files and merge into one dataset. Thanks and Regards, Xing [[alternative HTML version deleted]]

Does any one have a sample code for a Spider Plot as attached? Thanks, Xing

Dear R groups: I have the data as follows, I want to plot the "Rank1 ~ obs30*Cases" and "Rank2 ~ obs30*Cases" on the same plot as one 3-D scatter plot, how to do that? Any help is highly appreciated. ID obs30 Cases RANK1 RANK2 1 0.03175 63 82 81 2 0.00000 34 1 34 3 0.00000 36 2 41 4 0.00000 54 3 26 5 0.00000 22 4 42 6 0.00746 134 39 32 7 0.00000 2 5 53 8 0.01190 168 46 31

>2) Under MacOS 10.2.2. Given the following dataset: > > > summary(missing.data) > Hosp..No. Category Offset Side > r060093: 4 F Post op 0.5 year :62 Min. :-5.8333 L: 63 > r023250: 3 E Pre op 0.5 year :54 1st Qu.:-0.4167 R:141 > r026316: 3 H Post op 1.5 years :44 Median : 7.7083 > r032583: 3 G Post op 1 year

Dear Group: What is the best reference book on data manipulation with R in the market now? Thanks, XING

Dear all, I'm trying reproduce an example of bioassays Yielding Concentration-Mortality Data particularly control - adjustment model from book Bioassay of Entomopathogenic Microbes and Nematodes chapter 7 with R. I used glm with family=binomial and link=probit, but I do not know how to implement parameter gamma (control mortality - mortality of the untreated control insect in this exaple)

I've rolled up R-0.99.0.tgz a moment ago. You can get it from ftp://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or http://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or wait for it to be mirrored at a CRAN site near you within a day or two. There's also a version split in three (!) for floppies if you prefer that. The next release is to be 1.0.0 at the end of this month,

I've rolled up R-0.99.0.tgz a moment ago. You can get it from ftp://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or http://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or wait for it to be mirrored at a CRAN site near you within a day or two. There's also a version split in three (!) for floppies if you prefer that. The next release is to be 1.0.0 at the end of this month,

Consider the following situation: we have quantified algal concentrations for a variety of species using many samples at each of three years. It seems to make sense to generate a line plot (matplot-like), with each species plotted as a separate line, with the points connected to emphasize the temporal pattern. The problem: lots of overlapping error bars. The question: from both a

Hi, I want to plot grouped bars to compare 95% confidence interval estimates from two models. Each bar represents a 95% confidence interval estimate of a coefficient from one of the two models. Each group represents confidence interval estimates of the same coefficient from the two models. I think such a bar plot will nicely present whether 95% confidence interval estimates of the same

I have a mortality data over many years and I wish to plot the data and also add some smoother to clearly highlight the trend. How could I do that in R with base graphics or ggplot? I have the following sample data: require(lubridate) mdate<-seq(ymd('2000-01-01'),ymd('2010-12-31'), by = '1 day') death<- rnorm(4018, 80, 45) df<-cbind(mdate,death)

Hi everyone, We are looking for some data sets working with relative risk mortality. so, someone know where can I find the data.mgus dataset and the data.mgus? Using 1384 records from Minnesota. This data set are used in the : Robert A. Kyle, Terry M. Therneau, S. Vincent Rajkumar, Janice R. Offord, Dirk R. Larson, Matthew F. Plevak, and L. Joseph Melton III. A long-term study of prognosis in

Dear R-users, I have some human serum lipid concentrations (cholesterol, apoB ...), each lipid was measured (in the same person) for 6 times in different time points (start, 3 months, 6 months, 12 months, 18 months, 24 months). There were 2 groups of participants: one with a nutritional intervention and the other without it. I would like to know, whether lipid concentrations differ among different

Hi folks, Can someone please help me in identifying the type of plot shown here? Sample R code or specific package name would be of help as well. Thanks, -Girish http://www.nabble.com/file/p24477714/example_plot.jpg -- View this message in context: http://www.nabble.com/Help-needed-in-identifying-type-of-plot-tp24477714p24477714.html Sent from the R help mailing list archive at Nabble.com.

Dear R-users, I computed a simple coxph model and plotted survival over time with associated confidence intervals for 2 covariate levels (males and females). M1 <- coxph(survobject~sex, data=surv) M1 survsex <- survfit(survobject~sex,data=surv) summary(survsex) plot(survsex, conf.int=T, col=c("black","red"), lty = c(1,2), lwd=c(1,2), xlab="Time",

Hi All, I am relatively new to R (took a class 2 yrs ago ...), and am hoping someone can point me in the right direction for a problem I'd like to solve in R : I would like to calculate the relative mortality of a particular impairment, relative to the standard population. I.e. I'm trying to find S_relative(t) in the eqn below : S_impar(t) = S_standard(t) * S_relative(t) where

Hello, I have placed a package on CRAN about two surveys of mortality in Iraq that were published in the Lancet. http://cran.at.r-project.org/src/contrib/Descriptions/lancet.iraqmortality.html > install.packages("lancet.iraqmortality") ... > library(lancet.iraqmortality) Loading required package: foreign > ?lancet.iraqmortality > vignette("mortality") This is

Hello, I have placed a package on CRAN about two surveys of mortality in Iraq that were published in the Lancet. http://cran.at.r-project.org/src/contrib/Descriptions/lancet.iraqmortality.html > install.packages("lancet.iraqmortality") ... > library(lancet.iraqmortality) Loading required package: foreign > ?lancet.iraqmortality > vignette("mortality") This is

Dear all, I've used glm(family=binomial(link="logit")) several times, but now I think that a log link is more appropriate. I want to fit a model for probability of tree fall (TF)), with tree diameter (dbh) and soil moisure (soil) as predictors. A large number of trees have been checked every second year whether they stand up (0) or have fallen (1). I assume that the tree fall