fev: Forced Expiratory Volume (FEV) Data (fev)
In tmle: Targeted Maximum Likelihood Estimation
fev R Documentation
Forced Expiratory Volume (FEV) Data (fev)
Description
Sample of 654 youths, aged 3 to 19, in the area of East Boston
during middle to late 1970's. Interest concerns the relationship
between smoking and FEV. Since the study is necessarily
observational, statistical adjustment via regression models
clarifies the relationship.
Usage
data(fev)
Format
A data frame with 654 observations on the following 5 variables.
agea numeric vector
feva numeric vector
hta numeric vector
sexa numeric vector
smokea numeric vector
Source
Kahn M (2005). An Exhalent Problem for Teaching Statistics. The Journal of Statistical Education, 13(2).
Rosner, B. (1999), Fundamentals of Biostatistics, 5th Ed., Pacific Grove, CA: Duxbury.
tmle documentation built on Aug. 23, 2023, 1:08 a.m.
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| fev | R Documentation |
Forced Expiratory Volume (FEV) Data (fev)
Description
Sample of 654 youths, aged 3 to 19, in the area of East Boston during middle to late 1970's. Interest concerns the relationship between smoking and FEV. Since the study is necessarily observational, statistical adjustment via regression models clarifies the relationship.
Usage
data(fev)Format
A data frame with 654 observations on the following 5 variables.
agea numeric vector
feva numeric vector
hta numeric vector
sexa numeric vector
smokea numeric vector
Source
Kahn M (2005). An Exhalent Problem for Teaching Statistics. The Journal of Statistical Education, 13(2).
Rosner, B. (1999), Fundamentals of Biostatistics, 5th Ed., Pacific Grove, CA: Duxbury.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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