plm

问题 Is it possible to estimate a repeated measures random effects model with a nested structure using plm() from the plm package? I know it is possible with lmer() from the lme4 package. However, lmer() rely on a likelihood framework and I am curious to do it with plm() . Here's my minimal working example , inspired by this question. First some required packages and data, # install.packages(c("plm", "lme4", "texreg", "mlmRev"), dependencies = TRUE) data(egsingle, package = "mlmRev") the data-set

问题 Is it possible to estimate a repeated measures random effects model with a nested structure using plm() from the plm package? I know it is possible with lmer() from the lme4 package. However, lmer() rely on a likelihood framework and I am curious to do it with plm() . Here's my minimal working example , inspired by this question. First some required packages and data, # install.packages(c("plm", "lme4", "texreg", "mlmRev"), dependencies = TRUE) data(egsingle, package = "mlmRev") the data-set

问题 Is it possible to estimate a repeated measures random effects model with a nested structure using plm() from the plm package? I know it is possible with lmer() from the lme4 package. However, lmer() rely on a likelihood framework and I am curious to do it with plm() . Here's my minimal working example , inspired by this question. First some required packages and data, # install.packages(c("plm", "lme4", "texreg", "mlmRev"), dependencies = TRUE) data(egsingle, package = "mlmRev") the data-set

问题 I'm a new R user and I'm trying to use panel data (fixed effects) to analyse the effect that several independent variables have on the log of GNI. I'm using the plm package, and this is my code library(plm) head(project_data) Y = cbind(project_data$log_GNI_PPP) X = cbind(project_data$EU_application, project_data$EU_membership, project_data$distance_from_brussels, project_data$Former_USSR_DUMMY, project_data$natural_resources_pct, project_data$secondary_attendence_prct, project_data$eu

问题 I have a weird problem when estimating a random effects with the plm package in R. Here is a link to a dput of part of my data: https://pastebin.com/raw/mTdh26dg My code is: library(plm) library(haven) pmales <- pdata.frame(males_part, index = c("NR", "YEAR")) random <- plm(WAGE ~ SCHOOL + EXPER + EXPER2 + BLACK + HISP + MAR + UNION + RUR + NE + NC + S + factor(YEAR), data = pmales, model = "random") The reason I included libary(haven) is that my original data set is a .dta file. When I run

问题 I have a weird problem when estimating a random effects with the plm package in R. Here is a link to a dput of part of my data: https://pastebin.com/raw/mTdh26dg My code is: library(plm) library(haven) pmales <- pdata.frame(males_part, index = c("NR", "YEAR")) random <- plm(WAGE ~ SCHOOL + EXPER + EXPER2 + BLACK + HISP + MAR + UNION + RUR + NE + NC + S + factor(YEAR), data = pmales, model = "random") The reason I included libary(haven) is that my original data set is a .dta file. When I run

问题 Is there a way to get plm() to calculate between R2 and overall R2 for me and include them in the summary() output? To clarify what I mean with between, overall, and within R2 see this answer on StackExchange. My understanding is that plm only calculates within R2. I am running a Twoways effects Within Model. A random example (adapted from here): library(plm) # Create some random data set.seed(1) x=rnorm(100); fe=rep(rnorm(10),each=10); id=rep(1:10,each=10); ti=rep(1:10,10); e=rnorm(100) y=x

问题 For the following panel data set: panel <- structure(list(uurwerk = structure(c(40, 40, 40, 40, 36, 1, 32, 36, 32, 32, 36, 36, 40, 40, 40, 40, 40, 38, 38, 38, 38, 60, 55, 40, 42, 42, 42), label = "hours/week work in fact (on average)", class = c("labelled", "numeric")), loon_c = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), label = "pay/salary [gross] mean int", class = c("labelled", "numeric")), mtr_loon = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0,

问题 For the following panel data set: panel <- structure(list(uurwerk = structure(c(40, 40, 40, 40, 36, 1, 32, 36, 32, 32, 36, 36, 40, 40, 40, 40, 40, 38, 38, 38, 38, 60, 55, 40, 42, 42, 42), label = "hours/week work in fact (on average)", class = c("labelled", "numeric")), loon_c = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), label = "pay/salary [gross] mean int", class = c("labelled", "numeric")), mtr_loon = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0,

问题 I have problem with Within and random effect method (it doesn't work). And I have no problem with pooling, between or first diffeences estimator -> it works. I have the same problem like R - Error in class(x) - plm - only within and random effects models. Here is the link to my data: https://www.dropbox.com/s/8tgeyhxeb0wrdri/my_data.xlsx?raw=1 (there are some financial measures and GDP growth for some countries) My code: proba<-read_excel("my_data.xlsx") attach(proba) Y<-cbind(GDP_growth) X<