similar to: Censored (Tobit) Regression method

Folks, Based on http://www.biostat.wustl.edu/archives/html/s-news/1999-06/msg00125.html I thought I should experiment with using survreg() to estimate tobit models. I start by simulating a data frame with 100 observations from a tobit model > x1 <- runif(100) > x2 <- runif(100)*3 > ystar <- 2 + 3*x1 - 4*x2 + rnorm(100)*2 > y <- ystar > censored <- ystar <= 0

Hi, How can I recover the variance-covariance matrix of the tobit model from the variance-covariance of the survreg? I first used to the survreg function and then I selected the variance matrix. However, the last parameter is log(scale) and not the variance of the standard deviation of the censored distribution as in the Tobit model. tobit<- survreg(Surv(y, y > 0, type ='left')~

Dear R-user: I have a left censored longitudinally measured data set with 4 variables such as sub (which is id), x (only covariate), y (repeatedly measured response) and w (weights) (note, ?-5? indicates the left censored value in the attached data set). I am using following R codes (?survival? library and ?survreg? package) for fitting a random effect tobit model for the left censored

I am using survreg from the survival package to run a left censored tobit model on “non-survival” data. I have to four questions that I hope someone can help me with: 1) Is there anything I should take into consideration when using frailty() to estimate random intercepts? 2) Is there anyway of extracting the estimated intercepts produced by survreg when using frailty()? 3) Can someone point

Hi, what is the best way to estimate a tobit(truncated) regression model in R ? Is there already a packet available ? Gruss Ralph Leonhardt -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Dear R users: I am using survreg for modeling left censored longitudinal data. When I am using the following code for fitting the tobit model I am getting some output with an warning message(highlighted with red color): > survreg(Surv(y, y>=0, type='left')~x + frailty(id), cytokine.data, weight=w, dist='gaussian', scale=1) Call: survreg(formula = Surv(y, y >= 0, type

Having read previous correspondance on this topic, am I right in using a gaussian distribution for a tobit model, one article suggests a normal distribution? Also, I want to censure at the upper bound, so, using the survival5 package I use: survreg(Surv(y,y<c,type="right")~x) for a censored regression. Could anybody who's had experience of this, confirm whether I'm in the

Hello! I'm thinking of applying a censored regression model to cross-sectional data, using either the tobit (package survival) or the censReg function (package censReg). The dependent variable is left and right-censored. My hopefully not too silly question is this: I understand that heteroskedasticity and nonnormal errors are even more serious problems in a censored regression than in an

Dear everyone: I am a new user of R. I have a dataset with a dependent variable (DV) censored at different values. The dataset looks like, conditions .....IDV1 IDV2 DV 1 2 4 89 1 6 6 75 1 4 5 0 ( DV<=70) ...... 2 3 5 15 2 5 5 0

Hello, I am working on a Tobit Model for a consumer good, left censored with zero. Relation: Sales of product depend on price, promotion (dummy), Season(dummy) and store (dummy) Used standard Tobitmodel with package(AER) vor a 48 week period: tobitmodel<-tobit(SALE~Price+Promotion+Season+Store,data= datatobit) Now I want to predict the values for week 49-52. Used predict device:

Hi all, I'm from Brazil. I fit a Tobit model to FLUID MILK CONSUMPTION (DEPENDENT VARIABLE) data using survreg (attached). I am confused about the output interpretation and I would like yours explanations. Thanks, Marcio Roberto Silva -------------- next part -------------- A non-text attachment was scrubbed... Name: Tobit model.pdf Type: application/pdf Size: 9018 bytes Desc: not

Dear R experts, I am currently working on a rather simple tobit regression, where the dependet variable is left-censored (>0). I would like to apply a Tobit regression and then use the parameters of this regression to make a prediction with new data. The intention behind this is to do an extrapolation. by using the VGAM or AER package, I already succeeded in getting fitted values. However

Dear All: I need some guidance in calculating a goodness-of-fit statistic for a Tobit Regression model. To develop the Tobit regression, I used the tobit() method from the AER package, which is basically a simpler interface to the survreg() method. I've read about pseudo R2 and C-index and was wondering if there is a package that calculates this for me. Also, is there a reason to select

Hi there, I need to run a Tobit Fixed Effects in a panel data with 4500 units for 8 years. It is a huge data set, my dependent variable is left truncated at zero, the distribution is skewed and my panel is balanced. Any suggestions on how to do that in R? I tried stuff like survreg, censReg, and tobit but none of them were satisfactory. Thanks, *Felipe Nunes* CAPES/Fulbright Fellow PhD

I start by doing a simple gaussian tobit by MLE: x1 <- runif(1000) # E() = 0.5 x2 <- runif(1000)*2 # E() = 1 x3 <- runif(1000)*4 # E() = 2 ystar <- -7 + 4*x1 + 5*x2 + rnorm(1000) # is mean 0 y <- ystar censored <- ystar <= 0 y[censored] <- 0 library(AER) m <- tobit(y ~ x1 + x2, left=0, data=D) summary(m) Which gives: Call:

Hello R-Users: I am want to use tobit regression for left censored panel/longitudinal data. Could you please provide me the name of "library" and/or "package" that will give me option of fitting tobit regression model for longitudinal data? Thank you. Sattar __________________________________________________ [[alternative HTML version deleted]]

Hi, I'm trying to fit a tobit regression model to some data. When fitting the exact same data in Stata, I have no problems at all, however R won't converge. Its not a maxiters thing, since I've tried increasing this already. I need to be able to fit the model in R since there are users of the code that don't have a Stata license. The code is: require(AER) left = 3.218476 x =

Hello, I have interval censored data, censored between (0, 100). I used the tobit function in the AER package which in turn backs on survreg. Actually I'm struggling with the distribution. Data is asymmetrically distributed, so first choice would be a Weibull distribution. Unfortunately the Weibull doesn't allow for zero values in time data, as it requires x > 0. So I tried the

Appreciate any suggestions regarding how to fit an unbalanced panel data to a Tobit model using R functions. I am trying to analyze how real estate capital expenditures (CapEx) are affected by market conditions using a panel Tobit model. The CapEx is either positive or 0, so it is censored. The data are unbalanced panel, including the CapEx of about 5000 properties over about 40 quarters, with the

Hi all! Do you know if there is any R function/package that can be used to estimate "tobit" models with panel data (e.g. with random individual effects)? In economics, a "tobit" model is a model with a dependent variable that is left-censored at zero. Hence, it is a special case of a survival model and can be estimated using the "survival" package (see e.g.