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COUNT (version 1.3.2)

loomis: loomis

Description

Data are taken from Loomis (2003). The study relates to a survey taken on reported frequency of visits to national parks during the year. The survey was taken at park sites, thus incurring possible effects of endogenous stratification.

Usage

data(loomis)

Arguments

Format

A data frame with 410 observations on the following 11 variables.
anvisits
number of annual visits to park
gender
1=male;0=female
income
income in US dollars per year, categorical: 4 levels
income1
<=$25000< dd="">
income2
>$25000 - $55000
income3
>$55000 - $95000
income4
>$95000
travel
travel time, categorical: 3 levels
travel1
<.25 hrs<="" dd="">
travel2
>=.25 - <4 hrs<="" dd="">
travel3
>=4 hrs

Source

from Loomis (2003)

Details

loomis is saved as a data frame. Count models typically use anvisits as response variable. 0 counts are included

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Loomis, J. B. (2003). Travel cost demand model based river recreation benefit estimates with on-site and household surveys: Comparative results and a correction procedure, Water Resources Research, 39(4): 1105

Examples

Run this code
data(loomis)
glmlmp <- glm(anvisits ~ gender + factor(income) + factor(travel), family=poisson, data=loomis)
summary(glmlmp)
exp(coef(glmlmp))
library(MASS)
glmlmnb <- glm.nb(anvisits ~ gender + factor(income) + factor(travel), data=loomis)
summary(glmlmnb)
exp(coef(glmlmnb))

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