airpollution: Air Pollution

Description Usage Format Details Source References Examples

Description

This example is a subset of data from Six Cities study, a longitudinal study of the health effects of air pollution (Ware, J. H. et al., 1984).

Usage

1

Format

A data frame with 128 observations on the following 5 variables.

id

identifies de number of the individual profile. This vector contains observations of 32 individual profiles.

wheeze

a numeric vector that identify the wheezing status (1="yes", 0="no") of a child at each occasion.

age

a numeric vector corresponding to the age in years since the child's 9th birthday.

smoking

a factor that identify if the mother smoke (1="smoke", 0="no smoke").

counts

a numeric vector corresponding to the replications of each individual profile.

Details

The data set presented by Fitzmaurice and Laird (1993) contains complete records on 537 children from Steubnville, Ohio, each woman was examined annually at ages 7 through 10. The repeated binary response is the wheezing status (1="yes", 0="no") of a child at each occasion. Although mother's smoking status could vary with time, it was determined in the first interview and was treated as a time-independent covariate. Maternal smoking was categorized as 1 if the mother smoked regularly and 0 otherwise.

Source

Fitzmaurice, G. M. and Laird, N. M. (1993). A Likelihood-Based Method for analyzing Longitudinal Binary Response. Biometrika, 80, 141-51.

References

Ware, J. H., Dockery, D. W., Spiro, A. III, Speizer, F. E. and Ferris, B. G., Jr. (1984). Passive smoking, gas cooking and respiratory health in children living in six cities. Am. Rev. Respir. dis., 129, 366-74.

Examples

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str(airpollution)

#####  dependence="MC2"
air2 <- bild(wheeze~age+smoking, data=airpollution, time="age",
        aggregate=smoking, dependence="MC2")

summary(air2)
getAIC(air2)
getLogLik(air2)
plot(air2)

#####  dependence="MC2R"
air2r <- bild(wheeze~age+smoking, data=airpollution, time="age",
            aggregate=smoking, dependence="MC2R")

summary(air2r)
getAIC(air2r)
getLogLik(air2r)
plot(air2r) 

plot(air2r, which=6, subSET=smoking=="0", main="smoking==0", ident=TRUE) 

Example output

'data.frame':	128 obs. of  5 variables:
 $ id     : int  1 1 1 1 2 2 2 2 3 3 ...
 $ wheeze : int  0 0 0 0 0 0 0 1 0 0 ...
 $ age    : num  -2 -1 0 1 -2 -1 0 1 -2 -1 ...
 $ smoking: Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
 $ counts : num  237 237 237 237 10 10 10 10 15 15 ...

Call:
bild(formula = wheeze ~ age + smoking, data = airpollution, time = "age", 
    aggregate = smoking, dependence = "MC2")

Number of profiles in the dataset:  32 

Number of profiles used in the fit:  32 

Log likelihood:  -802.6775 

AIC:  1615.355 

Coefficients:	
            Label      Value Std. Error t value  p-value
(Intercept)     1 -1.8938438 0.11121860 -17.028 0.000000
age             2 -0.1091834 0.04967081  -2.198 0.027939
smoking1        3  0.2515951 0.17310721   1.453 0.146111
log.psi1        4  2.1792732 0.18122585  12.025 0.000000
log.psi2        5  1.1149180 0.22213626   5.019 0.000001

Message:  0 
[1] 1615.355
[1] -802.6775

Call:
bild(formula = wheeze ~ age + smoking, data = airpollution, time = "age", 
    aggregate = smoking, dependence = "MC2R")

Number of profiles in the dataset:  32 

Number of profiles used in the fit:  32 

Log likelihood:  -795.6447 

AIC:  1603.289 

Coefficients:	
            Label      Value Std. Error t value  p-value
(Intercept)     1 -3.0423537 0.31056862  -9.796 0.000000
age             2 -0.1744941 0.07040281  -2.479 0.013193
smoking1        3  0.3868212 0.26892918   1.438 0.150328
log.psi1        4  0.3796031 0.48558943   0.782 0.434369
log.psi2        5 -0.3424664 0.51664765  -0.663 0.507419

Random effect (omega):	
     Value Std. Error 
 1.4748750  0.3065123 

Message:  0 
[1] 1603.289
[1] -795.6447

bild documentation built on May 2, 2019, 12:01 p.m.