similar to: fixed effects regression

i want to ask 2 questions. 1) can R do Random-effects GLS regression which i can get from Stata? the following result is frome Stata.can I get the alike result from R? xtreg lwage educ black hisp exper expersq married union, re Random-effects GLS regression Number of obs = 4360 Group variable (i) : nr Number of groups = 545 R-sq:

Hi everyone, I have tried to solve a simple problem for days but I can't figure out how to run it properly. If someone could give me a hint, this would be really great. Basically, I want to run a standard economist's fixed, and random effects regression (corresponds to xtreg in STATA) but with _variable_ weights (they correspond to changing industry shares in the market). Here is

Dear ALL, I'm trying to figure out what the percentage effects are in a logistic regression. To be more clear, I'm not interested in the effect on y of a 1-unit increase in x, but on the percentage effect on y of a 1% increase in x (in economics this is also often called an "elasticity"). For example, if my independent variables are in logs, the betas can be directly

Dear list, I have come across this issue: combn(letters[1:5], 3) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c" [2,] "b" "b" "b" "c" "c" "d" "c"

Dear all, How can one fit just a fixed effects model in R? lme() seems to require a random component, whereas I am just looking for something like STATA's "xtreg, fe" function. Thanks, Pijus ---- W: 212-588-7897 F: 212-446-1955 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi, I am trying to run a logistic regression to look at the risk of malaria infection in individuals. I want to account for intra household correlation and so want to include a household level random effect. I have been using the lmer command in lme4 package but am getting some strange results that are completely different to those I get using STATA. Can I just check that this is the correct

Can lme or lmer fit a plain regular fixed effects anova? Ie a model without a random effect, or have there be at least one random effect in order for these functions to work? Trying to run such, (1) without specifying a random effect produces an error, (2) specifying that there is no random effect does not produce the same output as an anova run in lm(); (2b) specifying that there is no

Dear all, my problem is following. I know Stata, but currently I have to use R. Could You please help in finding the analogy to R. (1) creating of City-Dummy. I know in Stata: g byte city=0 replace city=1 if city==12&year==2000 and (2) Create a Time-Dummy-Variable g byte T2000=0 replace T2000=1 if year==2000 (3) I need the City DUmmy for the following combination: I have the

Hi, is there a way to analyze subpopulations (e.g. women over 50, those who answered "yes" to a particular question) in a survey using Survey package? Other packages (e.g. Stata, SUDAAN) do this with a subpopulation option to identify the subpopulation for which the analysis shoud be done. I did not see this option in the Survey package. Is there another way to do this?

Dear R-helpers, First of all, sorry for those who have (eventually) already received that request. The mail has been bumped several times, so I am not sure the list has received it... and I need help (if you have time)! ;-) I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by

Dear R-helpers, I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by individuals. For those using Stata, the counterpart would be xtreg with the "fe" option, or areg with the "absorb" option and in both case the clustering is achieved with "vce(cluster

I know there is a simple answer, I am attempting to make a simple indexing issue too complex. Suppose I have a dataframe like the following: x y 1 5 8 2 8 9 3 1 2 4 6 8 5 9 8 Now suppose I simply wish to have a lagged indicator of x such that x y z 1 5 8 NA 2 8 9 5 3 1 2 8 4 6 8 1 5 9 8 6 in stata this would be gen z=x[N-1] or even x y z 1 5 8 NA 2 8 9 NA 3 1 2 NA 4 6 8 1 5 9 8 6 in

Dear Colleagues I have been fitting some multinomial logistic regression models using R (version 1.6.1 on a linux box) and Stata 7. Although the vast majority of the parameter estimates and standard errors I get from R are the same as those from Stata (given rounding errors and so on), there are a few estimates for the same model which are quite different. I would be most grateful if

Hello I would like to develop the use of R. Trying R and more particulary the cox model, I am surprised by discrepancies between results with stata and R for a cox model With the same data base, I get a hazard ratio (4.82) that is not the same obtained with stata (4.52) You will find attached the file leukemia.dta I used (Stata) Here are the codes for R library(foreign)

Hi folks I am using the lmer function (in the lme4 library) to analyse some data where individuals are clustered into sets (using the SetID variable) with a single fixed effect (cc - 0 or 1). The lmer model and output is shown below. Whilst the fixed effects are consistent with stata (using xtmixed, see below), the std dev of the random effect for SetID is very very small (3.5803e-05)compared to

Léandre BASSOLE PhD Student CNRS-CERDI 65 Bd Francois Mitterrand Boite Postale 320 63009 Clermont-Ferrand CEDEX 1 FRANCE Tel : +33 4 73 17 74 45 Fax : +33 4 73 17 74 28 ----- Forwarded Message ---- From: Leandre Bassole <leandrebassole@yahoo.co.uk> To: r-help@r-project.org Sent: Saturday, 27 October, 2007 8:41:05 PM Subject: Hi all!! I am a new user of R. I am very familar to Stata, but

Ted Harding said: > I can get the estimated RRs from > RRs <- exp(summary(GLM)$coef[,1]) > but do not see how to implement confidence intervals based > on "robust error variances" using the output in GLM. Thanks for the link to the data. Here's my best guess. If you use the following approach, with the HC0 type of robust standard errors in the

Hello, I am constructing a nomogram using cph and nomogram commands in Dr. Harrell's Design/RMS package. The HR that I obtain for dichotomous and categorical variables are identical to those that I obtain using STATA stcox. However, the inter-quartile HR I obtain for continuous variables is obviously different, since STATA gives me HR for each unit (year, centimeter, etc) like coxph would

I looked for examples of count data that might interest the students and found this project about dropout rates in Los Angeles High Schools. It is discussed in the UCLA stats help pages for the Stata users: http://www.ats.ucla.edu/stat/stata/library/count.htm and See: http://www.ats.ucla.edu/stat/stata/library/longutil.htm To replicate those results, I used R's excellent foreign package to

Hi everybody, I try to calculate and display the marginal effect(s) in a hierarchical model using lmer. Here is my model: m1<- lmer(vote2011~ Catholic + Attendance+ logthreshold + West + Catholicproportion+ (Catholic * Catholicproportion) + (Attendance*Catholicproportion) + Catholicproportion?+ (Catholic *Catholicproportion?)+ (Attendance* Catholicproportion?) + (1 + Attendance+ Catholic