A Handbook of Statistical Analyses Using R (3rd Edition)

Vignettes

- An Introduction to R
- Chapter Analysis of Variance
- Chapter Analyzing Longitudinal Data I
- Chapter Analyzing Longitudinal Data II
- Chapter Bayesian Inference
- Chapter Cluster Analysis
- Chapter Conditional Inference
- Chapter Data Analysis using Graphical Displays
- Chapter Density Estimation
- Chapter Generalized Additive Models
- Chapter Logistic Regression and Generalized Linear Models
- Chapter Meta-Analysis
- Chapter Missing Values
- Chapter Multidimensional Scaling
- Chapter Principal Component Analysis
- Chapter Quantile Regression
- Chapter Recursive Partitioning
- Chapter Simple Inference
- Chapter Simultaneous Inference and Multiple Comparisons
- Chapter Survival Analysis
- Errata
- Multiple Linear Regression

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Description Usage Format Details Source Examples

Age and body fat percentage of 25 normal adults.

1 | ```
data("agefat")
``` |

A data frame with 25 observations on the following 3 variables.

`age`

the age of the subject.

`fat`

the body fat percentage.

`gender`

a factor with levels

`female`

and`male`

.

The data come from a study investigating a new methods of measuring body composition (see Mazess et al, 1984), and give the body fat percentage (percent fat), age and gender for 25 normal adults aged between 23 and 61 years. The questions of interest are how are age and percent fat related, and is there any evidence that the relationship is different for males and females.

R. B. Mazess, W. W. Peppler and M. Gibbons (1984), Total body composition by
dual-photon (153Gd) absorptiometry. *American Journal of Clinical Nutrition*,
**40**, 834–839.

1 2 |

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