similar to: bias sampling

Hi dear all, I am trying to import a dataset from SPSS into R (R x64 2.15.0). I used both   read.spss("D:/Untitled2.sav", use.value.labels = TRUE, to.data.frame = TRUE, max.value.labels = Inf, trim.factor.names = FALSE,trim_values = TRUE, reencode = NA, use.missings = to.data.frame) & read.spss("D:\\Untitled2.sav", to.data.frame = TRUE, stringsAsFactors = FALSE)   but the

hi I have a problem with  Median in Survival. when I use S1=survfit(Surv(Time,Status)) the result shows the median but I cannot use it as numeric! S1$median in Null   Could u pleas help me. Many Many Tank You. Niloofar. [[alternative HTML version deleted]]

Hi all i''m trying to use wheneverize gem to schedule my mails and to run a specific file in controller.i tried but unable to send mails. i am using rails 2.3.8 and ruby 1.8.7 . ive followed the https://github.com/javan/whenever this link Thanks in advance -- You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To view this

When I run rake test:units I get this error: 292 tests, 350 assertions, 2 failures, 13 errors rake aborted! Command failed with status (1): [/usr/local/bin/ruby -I"lib:test" "/ usr/loc...] This error just showed up yesterday --- I have no idea how I caused it. Here is my gem list in case that helps: actionmailer (2.3.2, 2.2.2) actionpack (2.3.2, 2.2.2) activerecord (2.3.2, 2.2.2)

Question: How can I get access to the bias value of a boot statistic? Details: Boot function: boot(data, statistic, R, sim="ordinary", stype="i", strata=rep(1,n), L=NULL, m=0, weights=NULL, ran.gen=function(d, p) d, mle=NULL, ...) When I create an object, containing the bootstrap statistic (object <- boot (....))I can call it and will get an output

OS : Ubuntu 12.04 Now I use Backup <https://github.com/meskyanichi/backup> and Whenever<https://github.com/javan/whenever> gem to backup my database. When I run backup perform -t my_backup ,I can works. But when I check the task crontab -l ,it as this: 0 22 * * * /bin/bash -l -c ''backup perform -t my_backup'' Run cat /etc/crontab to check my cron configuration

Dear R Users, My question is overall and not necessarily related to R. Suppose we face to a situation in which MSE( Mean Squared Error) shows desired results but Bias shows undesired ones, Or in advers. How can we evaluate the results. And suppose, Both MSE and Bias are important for us. The ecact question is that, whether there is any combined measure of two above metrics. Thank you so

Hi: I have a few clarification questions about the elements returned by the coxph function used in conjuction with a frailty term. I create the following group variable: group <- NULL group[id<50] <- 1 group[id>=50 & id<100] <- 2 group[id>=100 & id<150] <- 3 group[id>=150 & id<200] <- 4 group[id>=200 & id<250] <- 5 group[id>=250

Hey there, I was wondering if someone could tell me if there's a package or command that allows me to compute a GINI coefficient using a vector of weights. Also the coefficient should be bias corrected. Diego Rojas [[alternative HTML version deleted]]

Hi All, I am a relative newbie to R and have the following problem I was trying to solve. I had taken a look at the 'sample selection' package but was having trouble applying it to my use case and was wondering if anyone out there had done something similar and could share code or documentation either using this package or any other packages. I have a website page that I am subjecting to

R 2.3.1 Windows XP Question: How can I obtain the values of BIAS and STD. ERROR from a bootstrap. Background: I am running a bootstrap: result2<-boot(1:400,regSEvssample,R=5000) and obtain the following results: Bootstrap Statistics : original bias std. error t1* 1.876602 -0.0001368616 0.1630380 I would like to get the values of ORIGINAL and BIAS. I can get the value of

> From: Duncan Murdoch <murdoch.duncan at gmail.com> > Let's try it: > > > m <- (2/5)*2^32 > > m > 2^31 > [1] FALSE > > x <- sample(m, 1000000, replace = TRUE) > > table(x %% 2) > > 0 1 > 399850 600150 > > Since m is an even number, the true proportions of evens and odds should > be exactly 0.5.

Hello again I have a file from SPSS in .sav format. when I run library(foreign) cvar<-as.data.frame(read.spss("c:\\NDRI\\cvar\\data\\cvar2rev3.sav")) I get a warning Warning message: c:\NDRI\cvar\data\cvar2rev3.sav: Compression bias (0) is not the usual value of 100. The data appear to be OK, but I am concerned. (I tried searching the archives and the documenation for data

I have to the treatment effect base on the observational data.And the treatment variable is multinomial rather than binary.Because the treatment assignment is not random,so the selection-bias exists.Under this condition,what's the best way to estimate the treatment effect? I know that if the treatment is binary,I can use propensity score matching using MatchIt package.But what about

Dear R users: In Prof. Harrell's library rms, calibrate.rms plot the Bias-corrected Probability and Apparent Probability. The latter one can be retrieved from class calibrate.default. But how to retrieve the former one. BW *Yao Zhu* *Department of Urology Fudan University Shanghai Cancer Center Shanghai, China* [[alternative HTML version deleted]]

Dear all, I stumbled upon what appears to be a troublesome issue when sampling from an ARIMA model (from Rob Hyndman's excellent 'forecast' package) that contains a seasonal AR component. Here's how to reproduce the issue. (I'm using R 2.9.2 with forecast 2.19; see sessionInfo() below). First some data: > x <- c( 0.132475, 0.143119, 0.108104, 0.247291, 0.029510,

Dear R users, I?m student of Master in Statistic and Data analysis, in New University of Lisbon. And now i?m writting my dissertation in variance estimation.So i?m using Survey Package to compute the principal estimators and theirs variances. My data is from Incoming and Expendire Survey. This is stratified Multi-stage Survey care out by National Statistic Institute of Mozambique. My domain of

Dear list, It looks to me that R samples random integers using an intuitive but biased algorithm by going from a random number on [0,1) from the PRNG to a random integer, e.g. https://github.com/wch/r-source/blob/tags/R-3-5-1/src/main/RNG.c#L808 Many other languages use various rejection sampling approaches which provide an unbiased method for sampling, such as in Go, python, and others

Hi folks, I'm trying to estimate bias-corrected percentile (BCP) confidence intervals on a vector from a simple for loop used for resampling. I am attempting to follow steps in Manly, B. 1998. Randomization, bootstrap and monte carlo methods in biology. 2nd edition., p. 48. PDF of the approach/steps should be available here: https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9 If

Dear R-Help List, I'm trying to implement Firth's (1993) bias correction for log-linear models. Firth (1993) states that such a correction can be implemented by supplementing the data with a function of h_i, the diagonals from the hat matrix, but doesn't provide further details. I can see that for a saturated log-linear model, h_i=1 for all i, hence one just adds 1/2 to each count,