similar to: Repeated measures with categorical data

Hola!! A ver si alguien puede ayudarme!! Para ajuste de modelos lineales normalmente uso Gretl. Ahora estoy empezando a hacerlo en R. Me gustaría saber si existe alguna función que haga un summary extendido como el de Gretl. Os pongo un ejemplo del summary de Gretl. Modelo 1: MCO, usando las observaciones 1968-1982 (T = 15) Variable dependiente: Invest              Coeficiente   Desv. Típica

Estimada comunidad, estoy tratando de hacer un grafico y no resulta (adjuntos datos). Se grafican la vble "con" en el eje X y "can" en el eje Y. Se agrupa por la vble "sol". Se deben agregar como lineas horizontales los valores de "can" asociados a "sol" "ControlAE" y "ControlAB", para lo que uso panel. Pero al agregar

Dear list, I'd like to create a visual plot of a clmm() I've fitted using the 'ordinal' package in R. It's possible to do this with a glm() by using the 'effects' package. For example: library(effects) data(BEPS) mod <- lm(political.knowledge ~ age + gender + vote, data=BEPS) eff <- effect("age", mod, default.levels=100) plot(eff,

Hola, Por si lo quieres con colores rellenando cada punto: #---------------- library(data.table) library(lattice) dat <- read.table("pba.csv", header=TRUE, dec=",", as.is=TRUE) row.names(dat) <- NULL dat <- as.data.table(dat) dat$mycol <- ifelse(dat$sol =="ControlAE", "red", dat$sol) dat$mycol <- ifelse(dat$mycol

Dear list members, I am estimating an ordinal generalized estimating equations (GEE) regression model on repeated measurements data. Is there any way (preferably in R) to test the proportional odds assumption of this model? Thanks in advance. Andreas [[alternative HTML version deleted]]

Dear List, I am using both the clm() and clmm() functions from the R package 'ordinal'. I am fitting an ordinal dependent variable with 5 categories to 9 continuous predictors, all of which have been normalised (mean subtracted then divided by standard deviation), using a probit link function. From this global model I am generating a confidence set of 200 models using clm() and the

Hi all, I am trying to fit a random effect  model to categorical response variable using package "ordinal" /"clmm". How can I find the correlation between random effects (random intercept and random slope)   Thanks in advance  Ana [[alternative HTML version deleted]]

Dear List,   I have some longitudinal data, each patient was followed at times 0, 12, 16, 24 weeks and measure severity of a illness (0-worse, 1-same, 2-better). So, longitudinal response is categorical.  I was wondering whether lmer in R can fit a model for this type of data. If so, how we code? Or any other function in R that can fit this type of longitudinal data? Any suggestion would be

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

Hello, I searched everywhere but I didn't find what I want, that is why I as the question here. Threads discussing this issue on this mailing list are already quite old. Does anybody know of a function in R which allows to estimate ordered probit/logit model with random coefficients. The only mixed effect model I found was clmm of the ordinal package but it only provides random intercepts. I

Hello Prof. Harrell and 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/

Hi, I would like to fit Logit models for ordered data, such as those suggested by Greene (2003), p. 736. Does anyone suggests any package in R for that? By the way, my dependent variable is ordinal and my independent variables are ratio/intervalar. Thanks, Iuri. Greene, W. H. Econometric Analysis. Upper Saddle River, NJ: Prentice Hall, 2003

Hola buenas a todxs, comento mi duda: Calculo la correlación entre dos variables (calculo por años que: mayor tasa de desempleo implica menos venta de coches) y me sale positiva la correlación por lo tanto tienen una relación directa. Mi duda: ¿para que esta prediccíón sea cierta, además de una correlación positiva tengo que calcular el nivel de significancia entre las dos variables? Saludos y

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Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

Hello all, I am unsure of how to interpret the output from a Generalized Estimating Equation analysis of an ordinal response. I hope someone can enlighten me. The analysis was done using package 'repolr'. The data consists of a Score on a 3-point scale from 56 Subjects after repeatedly washing their hands with soap. Two soap Products were tested, each panelist washed 10 times = 10

0down votefavorite <https://stats.stackexchange.com/questions/296569/how-to-obtain-random-slope-random-intercept-plots-for-categorical-response-varia#> I'm trying to generate a random slope random intercept plot after ordinal regression using the clmmfunction from the ordinal package in R. I have aggression levels which are categorical with six levels. Earlier, I made random intercept

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/

Hello, I have an experimental design where I would like to use separate ranking events to predict an independent ranking event. I have been using function clmm in the ordinal library but now realize that I am violating one of the assumptions. I have included a subset of the data. I am looking at how undergraduate students perceive the architecture and biological correctness of box and arrow

Hola: Hace como un mes pregunte si se podía desarrollar una barra de progreso que informara del progreso de una subida de datos a SQL Server desde R. Miguel Ángel me dio una orientacion de como enfocar el problema y al final lo he conseguido hacer usando el paquete snowfall. Ahora bien hay una parte del código que, aunque funciona no entiendo muy bien como, porque "adapte" un código