harvey.lsmeans {agridat} | R Documentation

## Average daily gain of 65 steers for 3 lines, 9 sires.

### Description

Average daily gain of 65 steers for 3 lines, 9 sires.

### Usage

    data("harvey.lsmeans")

### Format

A data frame with 65 observations on the following 7 variables.

`line`

  line of the dam

`sire`

  sire

`damage`

  age class of the dam

`calf`

  calf number

`weanage`

  calf age at weaning

`weight`

  calf weight at start of feeding

`adg`

  average daily gain

### Details

The average daily gain 'adg' for each of 65 Hereford steers.

The calf age at weaning and initial weight at the beginning of the test feeding is also given.

The steers were fed for the same length of time in the feed lot.

It is assumed that each calf has a unique dam and there are no twins or repeat matings.

Harvey (1960) is one of the earliest papers presenting least squares means (lsmeans).

### Source

Harvey, Walter R. (1960). Least-squares Analysis of Data with Unequal Subclass Numbers. Technical Report ARS No 20-8. USDA, Agricultural Research Service. Page 101-102.

Reprinted as ARS H-4, 1975. https://archive.org/details/leastsquaresanal04harv

### References

Also appears in the 'dmm' package as 'harv101.df' See that package vignette for a complete analysis of the data.

### Examples

    library(agridat)
    data(harvey.lsmeans)
    dat = harvey.lsmeans

    require(lattice)
    dotplot(adg ~ sire|line,dat,
            main="harvey.lsmeans", xlab="sire", ylab="average daily gain")

    ## Not run:
      # Model suggested by Harvey on page 103
      m0 <- lm(adg ~ 1 + line + sire + damage + line:damage + weanage +
               weight, data=dat)

      # Due to contrast settings, it can be hard to compare model coefficients to Harvey,
      # but note the slopes of the continuous covariates match Harvey p. 107, where his
      # b is weanage, d is weight
      # coef(m0)
      #       weanage       weight
      #  -0.008154879  0.001970446

      # A quick attempt to reproduce table 4 of Harvey, p. 109. Not right.
      # require(emmeans)
      # emmeans(m0,c('line','sire','damage'))

    ## End(Not run)

[Package agridat version 1.16 Index]