nutrition: Nutrition data

Description

This observational dataset involves three factors, but where several factor combinations are missing. It is used as a case study in Milliken and Johnson, Chapter 17, p.202. (You may also find it in the second edition, p.278.)

Usage

nutrition

Arguments

Format

A data frame with 107 observations and 4 variables:

age: a factor with levels 1, 2, 3, 4. Mother's age group.
group: a factor with levels FoodStamps, NoAid. Whether or not the family receives food stamp assistance.
race: a factor with levels Black, Hispanic, White. Mother's race.
gain: a numeric vector (the response variable). Gain score (posttest minus pretest) on knowledge of nutrition.

Details

A survey was conducted by home economists ``to study how much lower-socioeconomic-level mothers knew about nutrition and to judge the effect of a training program designed to increase their knowledge of nutrition.'' This is a messy dataset with several empty cells.

Examples

Run this code

# NOT RUN {
nutr.aov <- aov(gain ~ (group + age + race)^2, data = nutrition)

# Summarize predictions for age group 3
nutr.emmGrid <- emmeans(nutr.aov, ~ race * group, at = list(age="3"))
                   
emmip(nutr.emmGrid, race ~ group)

# Hispanics seem exceptional; but this doesn't test out due to very sparse data
cld(nutr.emmGrid, by = "group")
cld(nutr.emmGrid, by = "race")
# }