fevdata: Forced Expiratory Volume (FEV) Data
In coursekata: Packages and Functions for 'CourseKata' Courses
fevdata R Documentation
Forced Expiratory Volume (FEV) Data
Description
Data from: Fundamentals of Biostatistics
Notes from: Kahn, M.
Abstract
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.
Pedagogical Notes:
This is a versatile dataset that can be used throughout an introductory statistics course as
well as an introductory modeling course. It includes many issues from statistical adjustment
in observational studies, to subgroup analysis, quadratic regression and analysis of covariance.
Usage
fevdata
Format
A data frame with 654 observations on the following 5 variables:
AGEAge, in years
FEVForced expiratory volume, in liters
HEIGHTHeight, in inches
SEX0 = Female, 1 = Male
SMOKE0 = Non-smoker, 1 = Smoker
References
Kahn,M. (2003). Data Sleuth, STATS, 37, 24. http://jse.amstat.org/datasets/fev.txt
Rosner, B. (1999). Fundamentals of Biostatistics, Pacific Grove, CA: Duxbury
coursekata documentation built on Sept. 11, 2024, 8:42 p.m.
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| fevdata | R Documentation |
Forced Expiratory Volume (FEV) Data
Description
Data from: Fundamentals of Biostatistics Notes from: Kahn, M.
Abstract
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.
Pedagogical Notes:
This is a versatile dataset that can be used throughout an introductory statistics course as well as an introductory modeling course. It includes many issues from statistical adjustment in observational studies, to subgroup analysis, quadratic regression and analysis of covariance.
Usage
fevdata
Format
A data frame with 654 observations on the following 5 variables:
AGEAge, in years
FEVForced expiratory volume, in liters
HEIGHTHeight, in inches
SEX0= Female,1= MaleSMOKE0= Non-smoker,1= Smoker
References
Kahn,M. (2003). Data Sleuth, STATS, 37, 24. http://jse.amstat.org/datasets/fev.txt Rosner, B. (1999). Fundamentals of Biostatistics, Pacific Grove, CA: Duxbury
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