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AER (version 1.2-9)

ShipAccidents: Ship Accidents

Description

Data on ship accidents.

Usage

data("ShipAccidents")

Arguments

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.

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

Greene2003

Examples

Run this code
# NOT RUN {
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)
# }

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