Re: [R] ggplot2: using coord_trans for logit -> probability

Sorry I jumped the gun. That does not provide you with the same plot as gg2 that you are aiming for. -T On Wed, Apr 16, 2014 at 7:37 PM, Tim Marcella wrote: > I think all you have to do is add type="response" to your call for the > predictions. > > Does this work fo

Re: [R] ggplot2: using coord_trans for logit -> probability

; Professor, Psychology Dept. & Chair, Quantitative Methods > York University Voice: 416 736-2100 x66249 Fax: 416 736-5814 > 4700 Keele StreetWeb: http://www.datavis.ca > Toronto, ONT M3J 1P3 CANADA > > __ > R-help@r-proj

[R] Plot mlogit object

Hi, I cannot figure out how or if I even can plot the results from a nested multinomial logit model. I am using the mlogit package. Does anyone have a lead on any tutorials? Both of the vignettes are lacking plotting instructions. Thanks, Tim -- Tim Marcella [[alternative HTML

[R] Time interactions for coxph object

ic formula CSHR.shore.fly <- coxph(Surv(entry, exit, to == 1) ~ shore.cat, data glba.mod) My variable shore.cat is violating the proportional hazards assumption so I am trying to add in an interaction with time. Do I interact exit? entry? or the range of the two? Thanks, Tim -- Tim Marcella

[R] Nested Logit Model

fferent modeling approach? I am mainly interested in the probability of choosing to react (fly or dive) or not, and then once a reaction has been made, which one is chosen and how these decisions relate to perpendicular distance to the ship's pat

[R] Coding for segmented regression within a hurdle model

Hi, I am using a two part hurdle model to account for zero inflation and overdispersion in my count data. I would like to account for a segmented or breakpoint relationship in the binomial logistic hurdle model and pass these results onto the count model (negative binomial). Using the segemented

[R] Negative binomial models and censored observations

Hi, I am working with hurdle models in the pscl package to model zero inflated overdispersed count data and want to incorporate censored observations into the equation. 33% of the observed positive count data is right censored, i.e. subject lost to follow up during the duration of the study. Can t

[R] Calculating RMSE in R from hurdle regression object

Hi, My data is characterized by many zeros (82%) and overdispersion. I have chosen to model with hurdle regression (pscl package) with a negative binomial distribution for the count data. In an effort to validate the model I would like to calculate the RMSE of the predicted vs. the observed values