Weight gain in pigs for different treatments

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

Usage

data("woodman.pig")

Format

A data frame with 30 observations on the following 7 variables.

pen: pen
treatment: diet
pig: pig number
sex: sex
weight1: initial weight in pounds, week 0
weight2: final weight in pounds, week 16
feed: feed eaten in pounds
w0: initial weight
g: average weekly gain
h: half rate of change in growth

Details

Six pigs in each of 5 pens were fed individually. From each litter there were 3 males and 3 females chosen for a pen. Three different diet treatments were used.

Note: Woodman gives the initial weights to the nearest 0.5 pounds.

The w0, g, h columns are from Wishart 1938. Wishart used the weekly weight measurements (not available) to fit quadratic growth curves for each pig and then reported the constants. These are the data that are widely used by many authors.

Source

Woodman, Evans, Callow & Wishart (1936). The nutrition of the bacon pig. I. The influence of high levels of protein intake on growth, conformation and quality in the bacon pig. The Journal of Agricultural Science, 26, 546 - 619. Table V, Page 557. https://doi.org/10.1017/S002185960002308X

Wishart, J. (1938). Growth-rate determinations in nutrition studies with the bacon pig and their analysis. Biometrika, 30: 16-28. Page 20, table 2. https://doi.org/10.2307/2332221

References

Wishart (1950) Table 2, p 17.

Bernard Ostle (1963). Statistics in Research, 2nd ed. Page 455. https://archive.org/details/secondeditionsta001000mbp

Henry Scheffe (1999). The Analysis of Variance. Page 217.

Peter H Westfall, Randall Tobias, Russell D Wolfinger (2011). Multiple Comparisons and Multiple Tests using SAS. Sec 8.3.

Examples

if (FALSE) { # \dontrun{
  library(agridat)
  data(woodman.pig)
  dat <- woodman.pig
  
  # add day of year for each weighing
  dat <- transform(dat, date1=36, date2=148)
  plot(NA, xlim=c(31,153), ylim=c(28,214),
       xlab="day of year", ylab="weight")
  segments(dat$date1, dat$weight1, dat$date2, dat$weight2,
           col=as.numeric(as.factor(dat$treatment)))
  title("woodman.pig")

  # Average gain per week
  dat <- transform(dat, pen=factor(pen), treatment=factor(treatment),
                   sex=factor(sex))
  m1 <- lm(g ~ -1 + pen + treatment +sex + treatment:sex + w0, data=dat)
  anova(m1)
  # Compare diets. Results similar to Westfall 8.13
  libs(emmeans)
  pairs(emmeans(m1, "treatment"))
  # NOTE: Results may be misleading due to involvement in interactions
  #  contrast estimate    SE df t.ratio p.value
  #  A - B      0.4283 0.288 19 1.490   0.3179 
  #  A - C      0.5200 0.284 19 1.834   0.1857 
  #  B - C      0.0918 0.288 19 0.319   0.9456 
} # }