eggs: Nested data on lab testing of eggs

In faraway: Functions and Datasets for Books by Julian Faraway

Nested data on lab testing of eggs

Description

Consistency between laboratory tests is important and yet the results may depend on who did the test and where the test was performed. In an experiment to test levels of consistency, a large jar of dried egg powder was divided up into a number of samples. Because the powder was homogenized, the fat content of the samples is the same, but this fact is withheld from the laboratories. Four samples were sent to each of six laboratories. Two of the samples were labeled as G and two as H, although in fact they were identical. The laboratories were instructed to give two samples to two different technicians. The technicians were then instructed to divide their samples into two parts and measure the fat content of each. So each laboratory reported eight measures, each technician four measures, that is, two replicated measures on each of two samples.

Format

A data frame with 48 observations on the following 4 variables.

Fat

a numeric vector

Lab

a factor with levels I II III IV V VI

Technician

a factor with levels one two

Sample

a factor with levels G H

Source

Bliss, C. I. (1967). Statistics in Biology. New York: McGraw Hill.

Examples

data(eggs)
## maybe str(eggs) ; plot(eggs) ...

faraway documentation built on Aug. 23, 2022, 5:08 p.m.