PanelCount (version 1.0.1)

ProbitRE: A Probit Model with Random Effects

Description

Estimate a Probit model with random effects

Usage

ProbitRE(formula, id, data = NULL, delta = 1, method = "BFGS",
  lower = NULL, upper = NULL, H = 20, accu = 1e+10, verbose = 0)

Arguments

formula

Formula of the model

id

A vector that represents the identity of individuals, numeric or character

data

Input data, a data frame

delta

Variance of random effects on the individual level for ProbitRE

method

Searching algorithm, don't change default unless you know what you are doing

lower

Lower bound for estiamtes

upper

Upper bound for estimates

H

A vector of length 2, specifying the number of points for inner and outer Quadratures

accu

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

verbose

Level of output during estimation. Lowest is 0.

Value

• A list containing the results of the estimated model

See Also

Other PanelCount: CRE_SS; CRE; PLN_RE; PoissonRE

Examples

data(rt)
est = ProbitRE(isRetweet~fans+tweets+as.factor(tweet.id),
                    id=rt$user.id, data=rt)