similar to: GLM for Probit for Panel Data

Hello all I have been working to fix this for weeks now, It should be simple to fix. Please help Let me explain what I am doing, I have a data set for 65 countries over a period of 9 years (2000-2008). Each country has on an average say 2000 interviews, so that the total set has roughly 65*9*2000 data points/observations (of course there are missing vales as well). Now let me explain how are the

Hi I have been trying so many different things to get my Inverse Mills Ratio going for a Two stage Heckman Model, I have tried the following so far (the commands are listed below till teh point where I get an error), I get an error in the last sentence (marked in bold below), if this were successful then I could have used the IMR as a control in my OLS (which would be the OLS for the outcome

Hi I am working on a panel data, my data are clustered/grouped by the variable "yearctry", I am running the regression below, but I cant make the regression recognise "yearctry" as the panel variable in the regression myProbit<- glm(s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit"), data = adpopdata) Can

Hi Saurav! On Sun, Jul 12, 2009 at 6:06 PM, Pathak, Saurav<s.pathak08 at imperial.ac.uk> wrote: > I am new to R, I have to do a 2 step Heckman model, my selection equation is > below which I was successful in running but I am unable to proceed further, > > > > I have so far used the following command > > glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc +

I have so far used the following command glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit")) My question is 1. How do i discard the non significant selection variables (one out of the seven variables above is non-significant) and calculate the Inverse Mills Ratio of the significant variables 2. I need the inverse

Dear R users My data set is e > names(e) [1] "yearctry" "discent" "age" "gender" "gemeduc" "gemhhinc" "ref_group" "fearfail_ref" "knowent_ref" "nbgoodc_ref" [11] "nbstatus_ref" "estbbuso_ref" "lngdp" "lngdpsq"

Dear R users I have a data set which has five variables. One depenedent variable y, and 4 Independent variables (education-level, householdincome, countrygdp and countrygdpsquare). The first two are data corresponding to the individual and the next two coorespond to the country to which the individual belongs to. My data set does not make this distinction between individual level and country

I am typing the following on the command prompt: >variab = read.csv(file.choose(), header=T) >variab It lists 900,000 ( this is the total number of observations in "variab" ) minus 797124 observations and prompts the following message [ reached getOption("max.print") -- omitted 797124 entries ]] Is there a way to see the entire set of data, ie all of 900,000 obs, and

Hi I have a stata data set (.dta file) of size 600 MB, I need to import it in R and do a 2SLS multilevel analysis on the data set. I would eb grateful if help is provided for the first part of how to import this big file from Stata to R and then how to open the imported Stata file in R? Kindly help Thanks in advance -- Dr.Saurav Pathak PhD, Univ.of.Florida Mechanical Engineering Doctoral

Dear R users I have two questions, I have been on this problem for last 3 months, please help First question: *How can I use the lmer function for a three level probit ( ie please help me with the command syntax)?* The second question is, *how can I then subsequently calculate the Inverse Mills ratio after the above probit is calculated using lmer?* Is there any other way (if lmer does not do

Hi I am using Stata 10 and I need to import a data set in stata 10 to R, I have saved the dataset in lower versions of Stata as well by using saveold command in Stata. My RAM is 4gb and the stata file is 600MB, I am getting an error message which says : "Error: cannot allocate vector of size 3.4 Mb In addition: There were 50 or more warnings (use warnings() to see the first 50)" Thus

Hi I am using Stata 10 and I need to import a data set in stata 10 to R, I have saved the dataset in lower versions of Stata as well by using saveold command in Stata. My RAM is 4gb and the stata file is 600MB, I am getting an error message which says : "Error: cannot allocate vector of size 3.4 Mb In addition: There were 50 or more warnings (use warnings() to see the first

Dear R saviors, kindly address to this problem, I would really appreciate any takers. I am trying to resolve this issue of IMR in clustered (multilevel) cross-sectional panel data for more than two months now,. The characteristics of my dataset are as follows: - some 900 000 individuals - total of 60 countries - cross-sectional time series at the country level max 10 years, not all

hi, i am need to plot two or more sets of data in a 3d scatterplot, each set with different color. i tried Rcmdr, and the 3d scatterplot facility, based on rgl. that is what i need. but i cannot seem to code different sets of data differently. any help will be very helpful. i tried scatterplot3d, but it is difficult to get the right angle in it. i need to be able to rotate the axes, and

Hi, I need some suggestion on how I could modify the color on some rectangle that I have created using "image". In other words, I have a 5x5 matrix, say, m. m <- matrix(rnorm(25), nrow=5) I create a grid of rectangles by: image(m) Now I want to change the color of rectangle (3,3) to blue. I don't know how this could be done, and searching the web has

Hi, I am building an application where i need to have an admin interface from where the admin can assign permission for different methods (create, edit etc.) in controller based on roles . It should be similar to django administration, where we can assign permission on methods based on the role. How can i do the implementaton ? Can anybody give me some pointers on how to start ? Thanks and

Hi, I am trying to plot densities given on a two dimensional grid. My data is in the an external file, and is arranged in three columns: x, y, density how may i get a plot of this? i would like to get (1) a three dimensional plot and (2) a color coded two dimensional plot. I have tried using image(x, y, density) but i am asked to put the data in ascending order. i am not sure how i may

Hi All, I am trying to use loess to smooth a 2D image, and also obtain the standard error for every pixel. I see that the standard error does not make sense. For example, running the following: library(stats) x <- array(c(1:100), dim=c(100,100)) y <- t(x) v <- exp(-((x-50)^2+(y-50)^2)/30^2) s <- v*0.02 g_noise <- rnorm(10000, mean = 0, sd = s) f <- v + g_noise f.loess <-

Hi, For some reason I have been unable to use the predict function when I desire the standard error to be calculated too. For example, when I try the following: l<- loess(d~x+y, span=span, se=TRUE) p<- predict(l, se=TRUE) I get the following error message: Error in vector("double", length) : vector size cannot be NA In addition: Warning message: In N * M1 : NAs produced by

hi all, i am trying to make multi-color plots. that is, i generally use, plot(x, y, type="n") text(x, y, labels=class) here, the vector class denotes the class of each point. there are usually 3-4 classes of points. how may i display the different classes in different colors? thanks for any help. -- saurav