flu_weight: Flu, Body Weight and DNA methylation
In mztwinreg: Regression Models for Monozygotic Twin Data
Description
Usage
Format
Details
Description
An artificial dataset containing information on flu, body weight and DNA methylation at an immune system gene locus, as well as demographic variables.
Usage
1
data("flu_weight")
Format
A data frame with 200 observations on the following 7 variables.
DNAmetha numeric vector: DNA methylation fraction (ranging 0-1) at an immune system gene locus
FluNowa numeric vector: Presence of severe flu at the moment of sample collection
FluChilda numeric vector: History of recurrent flu during childhood
Gendera character vector: Pair's gender
Agea numeric vector: Pair's age
Weighta numeric vector: Body weight in kilograms
PairNuma numeric vector: Randomly assigned pair number
Details
As observed from this dataset, the individuals of the sample are sorted following two criteria: 1) twin pairs are put together (adjacent rows), and 2) all twins are discordant for present flu (FluNow).
The second condition is necessary only when using the log_dif function.
It is recommended pre-sorting all datasets used along with this R package following criterion "1" or criteria "1" and "2".
mztwinreg documentation built on May 2, 2019, 8:52 a.m.
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Description Usage Format Details
Description
An artificial dataset containing information on flu, body weight and DNA methylation at an immune system gene locus, as well as demographic variables.
Usage
1 | data("flu_weight")
|
Format
A data frame with 200 observations on the following 7 variables.
DNAmetha numeric vector: DNA methylation fraction (ranging 0-1) at an immune system gene locus
FluNowa numeric vector: Presence of severe flu at the moment of sample collection
FluChilda numeric vector: History of recurrent flu during childhood
Gendera character vector: Pair's gender
Agea numeric vector: Pair's age
Weighta numeric vector: Body weight in kilograms
PairNuma numeric vector: Randomly assigned pair number
Details
As observed from this dataset, the individuals of the sample are sorted following two criteria: 1) twin pairs are put together (adjacent rows), and 2) all twins are discordant for present flu (FluNow).
The second condition is necessary only when using the log_dif function.
It is recommended pre-sorting all datasets used along with this R package following criterion "1" or criteria "1" and "2".
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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