pln {endogeneity}R Documentation

Poisson Lognormal Model

Description

Estimate a Poisson model with a log-normally distributed heterogeneity term. Also referred to as Poisson-Normal model.

Usage

pln(
  form,
  data = NULL,
  par = NULL,
  method = "BFGS",
  init = c("zero", "unif", "norm", "default")[4],
  H = 20,
  verbose = 0,
  accu = 10000
)

Arguments

form

Formula

data

Input data, a data frame

par

Starting values for estimates

method

Optimization algorithm.

init

Initialization method

H

Number of quadrature points

verbose

Level of output during estimation. Lowest is 0.

accu

1e12 for low accuracy; 1e7 for moderate accuracy; 10.0 for extremely high accuracy. See optim

Value

A list containing the results of the estimated model

References

Peng, Jing. (2022) Identification of Causal Mechanisms from Randomized Experiments: A Framework for Endogenous Mediation Analysis. Information Systems Research (Forthcoming), Available at SSRN: https://ssrn.com/abstract=3494856

Examples

library(MASS)
N = 2000
set.seed(1)

# Works well when the variance of the normal term is not overly large
# When the variance is very large, it tends to be underestimated
x = rbinom(N, 1, 0.5)
z = rnorm(N)
y = rpois(N, exp(-1 + x + z + 0.5 * rnorm(N)))
est = pln(y~x+z)
est$estimates

[Package endogeneity version 2.0.1 Index]