similar to: Odds Ratio and OR CI

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

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

Hi, I'm trying to build a Forest Plot using the second and fourth columns in the table (test.csv) below. My code is the following: curated <- data.frame("test.csv") tmp <- curated$coef tmp1 <- curated$se_coef plt <- metaplot(tmp, tmp1, xlim = c(-.45, .45)) I keep getting the following error at the last line and am not sure why: Error in if (is.na(lower[i] + upper[i]))

Hi Keep your messages coppied to R helplist, others could give you answers too. See in line From: Rosa Oliveira [mailto:rosita21 at gmail.com] Sent: Tuesday, August 1, 2017 4:38 PM To: PIKAL Petr <petr.pikal at precheza.cz> Subject: Re: [R] Superscript and subscrib R for legend x-axis and y-axis and colour different subjects in longitudinal data with different colours Hi Pikal, I looked

Hi Rosa, You pass a vector to ggplot, which expects a data.frame. I am sure you meant to do this: point7$y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7 ggplot(point7, aes(time, y_point7)) + geom_line() HTH Ulrik On Wed, 19 Jul 2017 at 20:37 Rosa Oliveira <rosita21 at gmail.com> wrote: > Hi everyone, > > I?m trying to do a spaghetti plot and I

Hi, everyone, Before everything, thanks. Lots of thanks ;)!!!! I don?t think you understood everything I need to do. I want to write t_i instead of "Day in ICU? [i subscript for t] and y_ij instead of "CRP (mg/dL)? [ij superscript for y]. The label of the axis? :( Can you help me on that task? Thanks!!!!! Best, Rosa Oliveira > On 31 Jul 2017, at 10:28, Martin Maechler

Hi Martin see in line > -----Original Message----- > From: Martin Maechler [mailto:maechler at stat.math.ethz.ch] > Sent: Monday, July 31, 2017 10:52 AM > To: PIKAL Petr <petr.pikal at precheza.cz> > Cc: Rosa Oliveira <rosita21 at gmail.com>; r-help mailing list <r-help at r- > project.org> > Subject: Re: [R] Superscript and subscrib R for legend x-axis and

>>>>> PIKAL Petr <petr.pikal at precheza.cz> >>>>> on Mon, 31 Jul 2017 09:11:18 +0000 writes: > Hi Martin see in line >> -----Original Message----- From: Martin Maechler >> [mailto:maechler at stat.math.ethz.ch] Sent: Monday, July >> 31, 2017 10:52 AM To: PIKAL Petr <petr.pikal at precheza.cz> >> Cc:

Hi everyone, I?m trying to do a spaghetti plot and I know I?m doing all wrong, It must be. What I need: 15 subjects, each with measurements over 5 different times (t1, ..., t5), and the variable that I need to represent in the spaguetti plot is given by: PCR = b0 + b1 * ti + epsilon B0, - baseline of each subject B1 - trajectory of each subject over time (so multiply by t) Epsilon - error

> Hi Rosa > something like > plot(1,1, sub=expression(lambda^"2")) > So with your example, do you want something like > plot(c(1:5), CRP7raw[1,], type = "n", xlim=c(1,5), ylim=c(-10,5) , > xlab="Day in ICU", > ylab="CRP (mg/dL)", > sub = mtext(expression(lambda^2))) OOps! Either plot( ..., sub = *) or

I am trying to incorporate random effects (random intercept is good enough) to a proportional odds logistic regression model for ordinal outcomes. Could lme4 do this? I'd appreciate any input. Hakan Demirtas

To the list: What R commands will perform the score test on an ordered multinomial logit model to evaluate the proportional odds assumption? Many thanks. Mtichell Wachtel [[alternative HTML version deleted]]

The code library(Design) f <- lrm(y~x1+x2+x1*x2, data=data) plot(f) produces a plot of log odds vs x2 with 0.95 confidence intervals. How do I get a plot of odds ratios vs x2 instead? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Odds-ratios-from-lrm-plot-tp4033340p4033340.html Sent from the R help mailing list archive at Nabble.com.

Dear community, I am currently attempting to perform a (L1) penalized ordinal logistic regression with proportional odds. For the moment I only found R packages allowing to perform forward or backward continuation ratio model with several penalizations. Does anyone have a clue of what R package I could use ? I am not even quite sure that penalized logistic regression with proportional odds has

Dear Dr. Fieberg, you used a regression tree approach to explore ordinal data set in addition to the proportinal odds model. I find this very interesting. I would like to know, how good the results of the regression tree approach turned out in comparison to the proportional odds model. Since people very often treat ordinal data as continuous, I would like to know how successfull this strategy

Hello dear R-help mailing list, I wish to perform a non-parametric repeated measures anova. If what I read online is true, this could be achieved using a mixed Ordinal Regression model (a.k.a: Proportional Odds Model). I found two packages that seems relevant, but couldn't find any vignette on the subject: http://cran.r-project.org/web/packages/repolr/

mantelhaen.test() gives the exact conditional p-value (for independence) and confidence intervals (CIs)for the common odds ratio for a stratified 2x2 table. The epitools package by Tomas Aragon (available via CRAN) contains functions which use fisher.test() to calculate mid-p exact p-values and CIs for the CMLE odds ratio for a single 2x2 table. The mid-p p-value for independence for a stratified

For the following model, library(vcd) arth.polr <- polr(Improved ~ Sex + Treatment + Age, data=Arthritis) summary(arth.polr) where Improved is an ordered, 3-level response I'm looking for a *simple* way to test the validity of the proportional odds assumption, typically done via a score test for equal slopes/effects over the predictors. I do find a po.test= option in the repolr package

Dear all, I am looking for an R function which does stepwise selection cox model in r (delta chisq likelihood ratio test) similar to the stepwise, pe (0.05) lr: stcox in STATA. I am very thankful for any reply. Regards, Linda [[alternative HTML version deleted]]

I am trying to do logistic regression with a categorical predictor variable with the glm() function, family=binomial. Using glm() I would like to be able to calculate the confidence intervals of all three possible odds ratios for a factor (the factor has three categories). Three categories imply two columns of 0's and 1's in the design matrix, and two parameter estimates with their