similar to: Generalised Linear models in R-Studio

Dear R users, I'm hoping that more experienced users will be able to assist me in examining the model fit of a mixed generalised linear model. The example using the data 'bacteria' within the MASS package will hopefully illustrate what I would like to acheive; library(MASS) library(nlme) attach(bacteria) # y being output and the trt - treatment group being an explanatory variable.

Hi, I have recently been attempting to find the LD50 from two predicted fits (For male and females) in a Generalised linear model which models the effect of both sex + logdose (and sex*logdose interaction) on proportion survival (formula = y ~ ldose * sex, family = "binomial", data = dat (y is the survival data)). I can obtain the LD50 for females using the dose.p() command in the MASS

To whom this may concern, I would be very grateful if someone could give me some advice on where I am going wrong with a logistic regression I am trying to run. I am trying to run a logistic regression on an aggregated data set and have input the command: logistic.mod<-glm(x~Frequency+Location+Sex+Age.Group,family=binomial(link="logit"),data=earsag1.dat) where x is the count of my

Hi, I am working with a friend on a master's project. Our laboratory does a lot of statistical analysis using the R stats package and we also have a lot of under-utilised nvidia cards sitting in the back of our networked linux machines. Our idea is to coerce the linux nvidia driver to run some of our statistical analysis for us. Our first thought was to specifically code up a version of

Dear R users I have built several glmm models using glmmPQL in the following structure: m1<-glmmPQL(dev~env*har*treat+dens, random = ~1|pop/rep, family = Gamma) (full script below, data attached) I have tried all the methods I can find to obtain some sort of model fit score or to compare between models using following the deletion of terms (i.e. AIC, logLik, anova.lme(m1,m2)), but I

Dear list, Is there a generalised form of rbind/cbind for combining matrices/arrays into higher-D structures? ie. if I have: a <- matrix(2,2,2) b <- matrix(3,2,2) how can I get array(rep(c(3,2), each=4), c(2,2,2)) ? It seems like this would be the job of a generalised abind function: abind(a,b, along=1) == rbind(a,b) abind(a,b, along=2) == cbind(a,b) abind(a,b, along=3)

Hi, I am trying to figure out the observed acceptance rate and M, using generalised rejection sampling to generate a sample from the posterior distribution for p. I have been told my code doesn't work because I need to "take the log of the expression for M, evaluate it and then exponentiate the result." This is because R is unable to calculate high powers such as 545.501.

Dear R users, I have used the following model: M1 <- gls(Nblad ~ Concentration+Season + Concentration:Season, data=DDD, weights=varIdent(form=~ 1 | Season*Concentration)) to assess the effect of Concentration and Season on nitrogen uptake by leaves (Nblad). I accounted for the difference in variance across the factor levels by using the varIdent function. Then I wanted to perform multiple

Readers, I have been reading 'the r book' by Crawley and think that the generalised additive model is appropriate for this problem. The package 'gam' was installed using the command (as root) install.package("gam") ... library(gam) > library(gam) Loading required package: splines Loading required package: akima > library(mgcv) This is mgcv 1.3-25 Attaching

Dear R users I am analysing data from a group of twins and their siblings. The measures that we are interested in are all correlated within families, with the correlations being stronger between twins than between non-twin siblings. The measures are all calculated from survey answers and by definition have limited ranges (e.g. -5 to +5), though within the range they are approximately normally

Thanks, this makes sense. Is there a similar precedence reasoning behind why operator functions (`+` etc) can't be piped into? On Fri, Apr 21, 2023 at 11:52?PM Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 21/04/2023 4:35 a.m., Michael Milton wrote: > > I just checked out R-devel and noticed that the new "pipe extractor" > > capability coming in 4.3

On 21/04/2023 11:33 a.m., Michael Milton wrote: > Thanks, this makes sense. Is there a similar precedence reasoning behind > why operator functions (`+` etc) can't be piped into? Yes: > identical(quote(1 + 1), quote(`+`(1, 1))) [1] TRUE Duncan Murdoch

I'm afraid I don't understand. I know that parsing `+`(1, 1) returns a result equivalent to `1 + 1`, but why does that impose a restriction on parsing the pipe operator? What is the downside of allowing arbitrary RHS functions? [[alternative HTML version deleted]]

I just checked out R-devel and noticed that the new "pipe extractor" capability coming in 4.3 only works for the 4 extractor operators, but no other standard operators like +, *, %*% etc, meaning that e.g. mtcars |> as.matrix() |> _ + 1 |> colMeans() is a syntax error. In addition, we are still subject to the restriction that the functions on the RHS of a pipe can't have

On 21/04/2023 12:16 p.m., Michael Milton wrote: > I'm afraid I don't understand. I know that parsing `+`(1, 1) returns a > result equivalent to `1?+ 1`, but why does that impose a restriction on > parsing the pipe operator? What is the downside of allowing arbitrary > RHS functions? I thought the decision to exclude "_ + 1" happens after enough parsing has

Dear R-gurus: I have a question about lmer. Basically, I have a dataset, in which each observation records number of trials (N) and number of events (Y) given a covariate combination(X) and group id (grp_id). So, my dataset is in tabular form. (in case my explanation of tabular form is unclear, please see the link:

On 21/04/2023 4:35 a.m., Michael Milton wrote: > I just checked out R-devel and noticed that the new "pipe extractor" > capability coming in 4.3 only works for the 4 extractor operators, but no > other standard operators like +, *, %*% etc, meaning that e.g. mtcars |> > as.matrix() |> _ + 1 |> colMeans() is a syntax error. In addition, we are > still subject to

Hi guys, I'm really sorry to bother you with this but I'm really battling and can't find any info to solve my problem. Please have a look at my issue below and give me some guidance as to what could be causing it. Thanks in advance. Kindest regards David Wilson _______________________________ D c D a t a Tel +27 33 342 7003 Fax +27 33 345 4155 Cell +27 82 4147413

Hi Allstaters, Does anybody know if the R package can fit Generalised Additive Models?. Thanks indeed, Aurelio. atobias at ole.com ___________________________________________________________________ Consigue tu e-mail gratuito TERRA.ES Haz click en http://www.terra.es/correo/ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

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