feedlot {lsmeans} | R Documentation |
This is an unbalanced analysis-of-covariance example, where one covariate is affected by a factor. Feeder calves from various herds enter a feedlot, where they are fed one of three diets. The weight of the animal at entry is the covariate, and the weight at slaughter is the response.
data(feedlot)
A data frame with 67 observations on the following 4 variables.
herd
a factor with levels 9
16
3
32
24
31
19
36
34
35
33
, designating the herd that a feeder calf came from.
diet
a factor with levels Low
Medium
High
: the energy level of the diet given the animal.
swt
a numeric vector: the weight of the animal at slaughter.
ewt
a numeric vector: the weight of the animal at entry to the feedlot.
The data arise from a Western Regional Research Project conducted at New Mexico State University. Calves born in 1975 in commercial herds entered a feedlot as yearlings. Both diets and herds are of interest as factors. The covariate, ewt
, is thought to be dependent on herd
due to different genetic backgrounds, breeding history, etc. The levels of herd
ordered to similarity of genetic background.
Note: There are some empty cells in the cross-classification of herd
and diet
.
Urquhart NS (1982) Adjustment in covariates when one factor affects the covariate. Biometrics 38, 651-660.
require(lsmeans) feedlot.lm <- lm(swt ~ ewt + herd*diet, data = feedlot) # Obtain LS~means with a separate reference value of ewt for each # herd. This reproduces the last part of Table 2 in the reference lsmeans(feedlot.lm, ~ diet | herd, cov.reduce = ewt ~ herd)