R: Data on blood pressure body mass and age

derived {ggm} | R Documentation

## Data on blood pressure body mass and age

### Description

Raw data on blood pressure, body mass and age on 44 female patients, and covariance matrix for derived variables.

### Usage

    data(derived)

### Format

A list containing a dataframe `raw` with 44 lines and 5 columns and a symmetric 4x4 covariance matrix `S`.

The following is the description of the variables in the dataframe `raw`

`Sys`

  Systolic blood pressure, in mm Hg

`Dia`

  Diastolic blood pressure, in mm Hg

`Age`

  Age of the patient, in years

`Hei`

  Height, in cm

`Wei`

  Weight, in kg

The following is the description of the variables for the covariance matrix `S`.

`Y`

  Derived variable `Y=log(Sys/Dia)`

`X`

  Derived variables `X=log(Dia)`

`Z`

  Body mass index `Z=Wei/(Hei/100)^2`

`W`

  Age

### References

Wermuth N. and Cox D.R. (1995). Derived variables calculated from similar joint responses: some characteristics and examples. Computational Statistics and Data Analysis, 19, 223-234.

### Examples

    # A DAG model with a latent variable U
    G = DAG(Y ~ Z + U, X ~ U + W, Z ~ W)

    data(derived)

    # The model fitted using the derived variables
    out = fitDagLatent(G, derived$S, n = 44, latent = "U")

    # An ancestral graph model marginalizing over U
    H = AG(G, M = "U")

    # The ancestral graph model fitted obtaining the
    # same result
    out2 = fitAncestralGraph(H, derived$S, n = 44)

[Package ggm version 2.3 Index]