govtform {modeLLtest} | R Documentation |
Data from a study on Western European government formation duration. Data is at the country-level (N = 409). Variable names are taken directly from original dataset. The data is publicly available and has been included here with the endorsement of the author. Please see the original codebook for a more detailed description of the variables.
data(govtform)
A data frame with 410 rows and 18 variables. The following are taken from the codebook at Dr. Sona N. Golder's Harvard Dataverse Page.
names of countries used in analysis
unique number identifying each country
unique number identifying each country. Begins with country code, followed by cabinets 1 - n
the number of days between either an election or the resignation of the previous government and the day on which the new government is officially inaugurated
date on which a government took office. Format is YYMMDD
date on which a government left office. Format is YYMMDD
dichotomous variable that equals 1 if a government is the first to form after an election (more uncertainty) and 0 if it forms in an interelection period (less uncertainty)
dichotomous variable that equals 1 if the government is nonpartisan and 0 otherwise
a fraction representing the number of parties that have wone legislative seats. See codebook for more detail
the number of inconclusive bargaining rounds prior to a new government successfully forming
cabinet name identified by surname of prime minister (followed by a number if the PM presided over more than one cabinet)
dichotomous variable that equals 1 if a single party controls a majority of the legislative seats, 0 otherwise
measures the level of ideological polarization in the party system. See codebook for more detail
dichotomous variable that equals 1 if the outgoing government or formateur gets the first opportunity to form a new government, 0 otherwise. See codebook for more detail
dichotomous variable that equals 1 if a new government requires the explicit support of a legislative majority in order to take office, 0 otherwise. See codebook for more detail
interaction term made by multiplying the postelection variable with the legislative_parties variable
interaction term made by multiplying the postelection variable with the polarization variable
interaction term made by multiplying the postelection variable with the positive_parl variable
Dr. Sona N. Golder's Harvard Dataverse Page
Golder, S. N. (2010). Bargaining delays in the government formation process. Comparative Political Studies, 43(1), 3-32. https://doi.org/10.1177/0010414009341714
data(govtform) library(survival) library(coxrobust) library(modeLLtest) # Survival models with data from Golder (2010) golder_surv <- Surv(govform$bargainingdays) golder_x <- cbind(govtform$postelection, govtform$legislative_parties, govtform$polarization, govtform$positive_parl, govtform$post_legislative_parties, govtform$post_polariz, govtform$post_positive, govtform$continuation, govtform$singleparty_majority) colnames(golder_x) <- c("govtform$postelection", "govtform$legislative_parties", "govtform$polarization", "govtform$positive_parl", "govtform$post_legislative_parties", "govtform$post_polariz", "govtform$post_positive", "govtform$continuation", "govtform$singleparty_majority") govtform.cox <- coxph(govtform.surv ~ govtform.x, method = "efron", data = govtform) govtform.robust <- coxr(govtform.surv ~ govtform.x, data = govtform) # Comparing PLM to IRR methods of estimating the survival model obj_cvmf_golder <- cvmf(golder_surv ~ golder_x, method = "efron", data = govtform) obj_cvmf_golder