The 3.2.4-revised version turned out to give trouble for some of CRAN's
subsystems.
Accordingly, a rebadged version 3.2.5 is now released; it only differs in the
version number and a few clean-up items. If you have a working install of
3.2.4-revised there should be no reason to upgrade it.
You can get the source code from
http://cran.r-project.org/src/base/R-3/R-3.2.5.tar.gz
or wait for it to be mirrored at a CRAN site nearer to you.
For the R Core Team,
Peter Dalgaard
New md5 sums are
MD5 (AUTHORS) = eb97a5cd38acb1cfc6408988bffef765
MD5 (COPYING) = eb723b61539feef013de476e68b5c50a
MD5 (COPYING.LIB) = a6f89e2100d9b6cdffcea4f398e37343
MD5 (FAQ) = cd7bfa946b8650cb87807e94e46984c6
MD5 (INSTALL) = 3964b9119adeaab9ceb633773fc94aac
MD5 (NEWS) = 42d76ce7f8e80977d5043bca4234f4c9
MD5 (NEWS.0) = bfcd7c147251b5474d96848c6f57e5a8
MD5 (NEWS.1) = eb78c4d053ec9c32b815cf0c2ebea801
MD5 (NEWS.2) = e840d32b7ef7a7603455d30d6d54fda7
MD5 (R-latest.tar.gz) = 7b23ee70cfb383be3bd4360e3c71d8c3
MD5 (README) = aece1dfbd18c1760128c3787f5456af6
MD5 (RESOURCES) = 529223fd3ffef95731d0a87353108435
MD5 (THANKS) = ba00f6cc68a823e1741cfa6011f40ccb
MD5 (VERSION-INFO.dcf) = 661c20647b9f0b9fa980297c53438609
MD5 (R-3/R-3.2.5.tar.gz) = 7b23ee70cfb383be3bd4360e3c71d8c3
The relevant NEWS file entries (relative to 3.2.4) are
CHANGES IN R 3.2.5:
BUG FIXES:
? format.POSIXlt() behaved incorrectly in R 3.2.4. E.g. the output
of format(as.POSIXlt(paste0(1940:2000,"-01-01"), tz =
"CET"),
usetz = TRUE) ended in two "CEST" time formats.
? A typo in the Makefile for src/extra/xz prevented builds of
liblzma.a. (Notice that this will become unbundled in 3.3.0.)
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
Howdy everyone
I?m trying to get Odds ratio and OR confidence intervals using a probit model,
but I'm not getting.
Do you think you can help me?
I?m new with R L
naive =
summary(glm(pcr.data[,7]~boldBeta_individual+pcr.data$age,family=binomial(link=probit)))
naive_answer = c(naive$coefficients[,1:3])
#naive estimates for
#alpha (first 4 collumns: intercept; beta_intercept, beta_slope and age) and
#and SE(last 4 collumns: intercept; beta_intercept, beta_slope and age)
OR.naive = exp(1.6*coef(naive))
(till here works, the problem is with the confidence interval)
I tried to get the Standard error from the variance, but I?m not sure if this
can be done as I?ve done.
Var_coef <- 1.6^2*var(coef(naive))
SE_coef <- Var_coef/sqrt(nsample) ########## I thi k this
is correct
OR.naive.inf <- exp(OR.naive - (1.96 * SE_coef))
OR.naive.sup <- exp(OR.naive + (1.96 * SE_coef))
if I used logit link I would get the CI with confint(na?ve) command, but with
probit I don't think so. Is there a way?
What should I do?
Atenciosamente,
Rosa Oliveira
--
____________________________________________________________________________
Rosa Celeste dos Santos Oliveira,
E-mail: rosita21 at gmail.com <mailto:rosita21 at gmail.com>
Tlm: +351 939355143
Linkedin: https://pt.linkedin.com/in/rosacsoliveira
<https://pt.linkedin.com/in/rosacsoliveira>
____________________________________________________________________________
"Many admire, few know"
Hippocrates