cquad_ext: Conditional maximum likelihood estimation of the quadratic...

In cquad: Conditional Maximum Likelihood for Quadratic Exponential Models for Binary Panel Data

Conditional maximum likelihood estimation of the quadratic exponential model for panel data

Description

Fit by conditional maximum likelihood the model for binary longitudinal data proposed by Bartolucci & Nigro (2010).

Usage

cquad_ext(id, yv, X = NULL, be = NULL, w = rep(1, n),Ttol=10)

Arguments

id	list of the reference unit of each observation
yv	corresponding vector of response variables
X	corresponding matrix of covariates (optional)
be	initial vector of parameters (optional)
w	vector of weights (optional)
Ttol	Threshold individual observations that activates the recursive algorithm (default=10)

Value

formula	formula defining the model
lk	conditional log-likelihood value
coefficients	estimate of the regression parameters (including for the lag-response)
vcov	asymptotic variance-covariance matrix for the parameter estimates
scv	matrix of individual scores
J	Hessian of the log-likelihood function
se	standard errors
ser	robust standard errors
Tv	number of time occasions for each unit

Author(s)

Francesco Bartolucci (University of Perugia), Claudia Pigini (University of Ancona "Politecnica delle Marche"), Francesco Valentini (University of Ancona "Politecnica delle Marche")

References

Bartolucci, F. and Nigro, V. (2010), A dynamic model for binary panel data with unobserved heterogeneity admitting a root-n consistent conditional estimator. Econometrica, 78, pp. 719-733.

Examples

# example based on simulated data
data(data_sim)
data_sim = data_sim[1:500,]   # to speed up the example, remove otherwise
id = data_sim$id; yv = data_sim$y; X = cbind(X1=data_sim$X1,X2=data_sim$X2)
# static model
out = cquad_ext(id,yv,X,Ttol=10)
summary(out)

cquad documentation built on March 7, 2023, 6:15 p.m.