ShipAccidents {AER} | R Documentation |
Ship Accidents
Description
Data on ship accidents.
Usage
data("ShipAccidents")
Format
A data frame containing 40 observations on 5 ship types in 4 vintages and 2 service periods.
- type
factor with levels
"A"
to"E"
for the different ship types,- construction
factor with levels
"1960-64"
,"1965-69"
,"1970-74"
,"1975-79"
for the periods of construction,- operation
factor with levels
"1960-74"
,"1975-79"
for the periods of operation,- service
aggregate months of service,
- incidents
number of damage incidents.
Details
The data are from McCullagh and Nelder (1989, p. 205, Table 6.2) and were also used by Greene (2003, Ch. 21), see below.
There are five ships (observations 7, 15, 23, 31, 39) with an operation period
before the construction period, hence the variables service
and
incidents
are necessarily 0. An additional observation (34) has entries
representing accidentally empty cells (see McCullagh and Nelder, 1989, p. 205).
It is a bit unclear what exactly the above means. In any case, the models are fit
only to those observations with service > 0
.
Source
Online complements to Greene (2003).
https://pages.stern.nyu.edu/~wgreene/Text/tables/tablelist5.htm
References
Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall.
McCullagh, P. and Nelder, J.A. (1989). Generalized Linear Models, 2nd edition. London: Chapman & Hall.
See Also
Examples
data("ShipAccidents")
sa <- subset(ShipAccidents, service > 0)
## Greene (2003), Table 21.20
## (see also McCullagh and Nelder, 1989, Table 6.3)
sa_full <- glm(incidents ~ type + construction + operation, family = poisson,
data = sa, offset = log(service))
summary(sa_full)
sa_notype <- glm(incidents ~ construction + operation, family = poisson,
data = sa, offset = log(service))
summary(sa_notype)
sa_noperiod <- glm(incidents ~ type + operation, family = poisson,
data = sa, offset = log(service))
summary(sa_noperiod)
## model comparison
anova(sa_full, sa_notype, test = "Chisq")
anova(sa_full, sa_noperiod, test = "Chisq")
## test for overdispersion
dispersiontest(sa_full)
dispersiontest(sa_full, trafo = 2)