crampton.pig {agridat} | R Documentation

## Weight gain in pigs for different treatments

### Description

Weight gain in pigs for different treatments, with initial weight and feed eaten as covariates.

### Usage

    data("crampton.pig")

### Format

A data frame with 50 observations on the following 5 variables.

`treatment`

  feed treatment

`rep`

  replicate

`weight1`

  initial weight

`feed`

  feed eaten

`weight2`

  final weight

### Details

A study of the effect of initial weight and feed eaten on the weight gaining ability of pigs with different feed treatments.

The data are extracted from Ostle. It is not clear that 'replicate' is actually a blocking replicate as opposed to a repeated measurement. The original source document needs to be consulted.

### Source

Crampton, EW and Hopkins, JW. (1934). The Use of the Method of Partial Regression in the Analysis of Comparative Feeding Trial Data, Part II. The Journal of Nutrition, 8, 113-123.

### References

Bernard Ostle. Statistics in Research

Goulen. Methods of Statistical Analysis, 1st ed. Page 256-259.

### Examples

    data(crampton.pig)
    dat <- crampton.pig

    dat <- transform(dat, gain=weight2-weight1)
    require(lattice)
    # Trt 4 looks best
    xyplot(gain ~ feed, dat, group=treatment, type=c('p','r'),
           auto.key=list(columns=5),
           xlab="Feed eaten", ylab="Weight gain", main="crampton.pig")

    # Basic Anova without covariates
    m1 <- lm(weight2 ~ treatment + rep, data=dat)
    anova(m1)
    # Add covariates
    m2 <- lm(weight2 ~ treatment + rep + weight1 + feed, data=dat)
    anova(m2)
    # Remove treatment, test this nested model for significant treatments
    m3 <- lm(weight2 ~ rep + weight1 + feed, data=dat)
    anova(m2,m3) # p-value .07. F=2.34 matches Ostle

[Package agridat version 1.16 Index]