similar to: update not working

Dear R users, I noticed a problem in the anova command when applied on a single coxph object if there are missing observations in the data: This example code was run on R-2.6.1: > library(survival) > data(colon) > colondeath = colon[colon$etype==2, ] > m = coxph(Surv(time, status) ~ rx + sex + age + perfor, data=colondeath) > m Call: coxph(formula = Surv(time, status) ~ rx +

Hi R bayesians, I need an advise how to resolve the two different estimates applying a traditional glm (TG) and a bayes glm (BG), and different results depending on the data formats of response data and the prior specs using bayesglm in R. I'm not familiar with bayes estimate and my colleague asked me to look into this because the EPA from France reported a quite different estimates for

Dear all, Is there anybody who can help me to avoid scientific number in the summary of an lm model? Here there is an example of a usual output of the lm model. Thank you! Guillermo Example summary(lm(promiscuity.Index~allK)) Call: lm(formula = promiscuity.Index ~ allK) Residuals: Min 1Q Median 3Q Max -1.67094 -0.13126 0.06703 0.19913 0.40673 Coefficients:

Hi, I have a question about how I should report the results for a linear mixed effects model where the model includes as predictors three factors (facA, facB and facC), one of which (facA) interacts with the other two. facA and facB have two levels and facC has 3 levels. There are also several other continuous predictors (e.g. varA, varB, varC). My mixed model is specified with the following

Dear All- I have a dataset that is comprised of the following: doy yr mon day hr hgt1 hgt2 hgt3 co21 co22 co23 sig1 sig2 sig3 dif flag 244.02083 2005 09 01 00 2.6 9.5 17.8 375.665 373.737 373.227 3.698 1.107 0.963 -0.509 PRE 244.0625 2005 09 01 01 2.6 9.5 17.8 393.66 384.773 379.466 15.336 11.033 5.76 -5.307 PRE 244.10417 2005 09 01 02 2.6 9.5 17.8 411.162 397.866 387.755 6.835 5.61 6.728

Dear Adrian and Ian (and r-helpers), I encountered a curious result in developing an example using the bicreg function in the BMA package: I noticed that pairs of models with equal R^2 and equal numbers of predictors had nevertheless different BIC values. Looking at the bicreg function, the definition of BIC appears to be the usual one, or close to it [bic <- n * log(1 - r2/100) + (size - 1) *

Hello all: I am confused about the output from a lm() model with an incomplete design/missing level. I have two categorical predictors and a continuous covariate (day) that I am using to model larval mass (l.mass): leaf.species has three levels - map, syc, and oak cond.time has two levels - 30 and 150. There are no response values for Map-150, so that entire, two-way, level is missing.

Dear experts, I just noticed that I get different results conducting type III anova using drop1 or the Anova command from the car package. I suppose I made a mistake and hope you can offer me some help. I have no idea where I got wrong and would be very grateful for explaination as R is new terrain for me. If I run the commands in line, they produce the same results. But if I run them in

Full_Name: Tao Shi Version: 1.7.0 OS: Windows XP Professional Submission from: (NULL) (149.142.163.65) > x [,1] [,2] [1,] 149 151 [2,] 1 8 > c2x<-chisq.test(x, simulate.p.value=T, B=100000)$p.value > for(i in (1:20)){c2x<-c(c2x,chisq.test(x, simulate.p.value=T,B=100000)$p.value)} > c2tx<-chisq.test(t(x), simulate.p.value=T, B=100000)$p.value > for(i in

Hello r-list members, I've been doing some linear modeling with a dataset structured as follows. Tubes containing 500 larvae of Trichinella each were treated with one of four different temperatures. Each day (or every 10 days depending on treatment group), 3 tubes were selected from each treatment and all the dead larvae were counted. The tubes were discarded. Final larvae counts were

Hi, I would like to know whether it is possible to obtain a value of significance for random effects when aplying the lme or related functions. The default output in R is just a variance and standard deviation measurement. I feel it would be possible to obtain the significance of these random effects by comparing models with and without these effects. However, I'm not used to perform

I have a large number of troff help files which are automatically converted to .Rd files. Many of these have examples which contain the printed output of the examples. This makes example(functionname) not work. Is there a way to avoid removing all this output by delimiting it in some way such that the output will not appear in R-ex? Secondly, it would be nice if there was a place where output

Hi! I'm running an anova on a lm and I get the message Error: invalid dimnames given for data frame Any idea where it comes from? Many thanks. Here is the fit and the attempted anova: > fit Call: lm(formula = as.formula(paste(chemical, "a~", cmd, sep = "")), singular.ok = TRUE) Coefficients: (Intercept) Odom Displace Weight

Most of libc++ doesn't have explicit template instantiations, which leads to a pretty significant build time and code size cost when using libc++, since a large number of common templates will be emitted by the compiler and coalesced by the linker. Notably, in include/__config, we have: #ifndef _LIBCPP_EXTERN_TEMPLATE #define _LIBCPP_EXTERN_TEMPLATE(...) #endif whereas before

Hallo, I have this dataset with repeated measures. There are two within-subject factors, "formant" (2 levels: 1 and 2) and "f2 Ref" (25 levels: 670, 729, 788, 846, 905, 1080, 1100, 1120, 1140, 1170, 1480, 1470, 1450, 1440, 1430, 1890, 1840, 1790, 1740, 1690, 2290, 2210, 2120, 2040, 1950), and one between-subject factor, lang (2 levels:1 and 2). The response variable

Dear R list, members of my course have encountered the following error message: > slm <- lm(price ~ engsize, autoframe) Error in get(x, envir, mode, inherits) : variable "FUN" was not found [more context is given in the fuller listing below]. Once the error is encountered it seems to persist; for example early in one session: > summary(blin.fit) Call: lm(formula = Response

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Hello folks, TL;DR: This is my proposed hashing interface based on a proposed standard hashing interface. It also is implemented with a much faster and higher quality algorithm than the current one. This is an *early draft* of the code, looking for initial feedback. There has been recent interest in improving the quality and consistency of LLVM's approach to hashing. In particular, getting

Hello, I tryed out spandsp with libtiff-3.5.7 and with Asterisk from CVS. I tryed to receive a fax on a CAPI channel. Finally I got a file with 8 byte length (/tmp/testfax.tif). How can I do next? Thanks in advance, Thomas ps: what are hardware requirements for sending/receiving faxes? -- creating pipe for PLCI=0x101 msn = 2258589 > sent ALERT_REQ PLCI = 0x101 --

Hello, I have attached a model file which can be used to rank new queries. Disclaimer: I don't remember if its is the updated one or the one with which I evaluated the API before. But it should work with your new queries with libsvm based letor module. Parth. -------------- next part -------------- An HTML attachment was scrubbed... URL: