This data set consists of 654 observations on youths aged 3 to 19 from East Boston recorded duing the middle to late 1970's. Forced expiratory volume (FEV), a measure of lung capacity, is the variable of interest. Age and height are two continuous predictors. Sex and smoke are two categorical predictors.

data(fev)

Format

A data frame with 654 observations on 5 variables.

age

Age (years)

fev

Forced expiratory volume (liters). Roughly the amount of air an individual can exhale in the first second of a forceful breath.

height

Height (inches).

sex

Female is 0. Male is 1.

smoke

A binary variable indicating whether or not the youth smokes. Nonsmoker is 0. Smoker is 1.

Details

Copies of this data set can also be found in the coneproj and tmle packages.

References

Tager, I. B., Weiss, S. T., Rosner, B., and Speizer, F. E. (1979). Effect of parental cigarette smoking on pulmonary function in children. American Journal of Epidemiology, 110, 15-26.

Rosner, B. (1999). Fundamentals of Biostatistics, 5th Ed., Pacific Grove, CA: Duxbury.

Kahn, M.J. (2005). An Exhalent Problem for Teaching Statistics. Journal of Statistics Education, 13(2). http://www.amstat.org/publications/jse/v13n2/datasets.kahn.html

Examples

data(fev)
full.mod = lm(fev~.,data=fev)
step(full.mod)
#> Start:  AIC=-1154.18
#> fev ~ age + height + sex + smoke
#> 
#>          Df Sum of Sq    RSS      AIC
#> <none>                110.28 -1154.18
#> - smoke   1     0.368 110.65 -1154.00
#> - sex     1     3.803 114.08 -1134.00
#> - age     1     8.099 118.38 -1109.83
#> - height  1    81.505 191.78  -794.28
#> 
#> Call:
#> lm(formula = fev ~ age + height + sex + smoke, data = fev)
#> 
#> Coefficients:
#> (Intercept)          age       height          sex        smoke  
#>    -4.45697      0.06551      0.10420      0.15710     -0.08725  
#>