antlers: Simulated data on the effects of diet on deer antlers

In brouwern/compbio4all: Datasets and helpful functions for learning bioinformatics and computational biology

Description

Data simulated based on summary information in Asleson et al. (1997). Deer were fed three different diets that varied in the timeing of high protein. Data are suitable for analysis with 1-way ANOVA.

Usage

antlers

Format

A data frame

diet

Experimental diet during both spring and summer. Hi.Hi = High quality diet in both season. Hi.Lo = high quality diet in spring but poor in summer.

mass

Antler mass in grams

circum

basal circumference in mm

beam

Length of main beam of antler in mm

spread

spread between points in mm

Details

See the vignette "Intro to 1-way ANOVA: impacts of diet on deer antlers" for a thorough exploration of these data. The examples below demonstate basic plotting and 1-way ANOVA.

References

Asleson et al. 1997. Effects of seasonal protein restriction on antlerogenesis and body mass in adult male white-tailed deer. Journal of Wildlife Management 61.

Examples

## Not run: 
## Load packages
library(ggplot2)
library(ggpubr)

## Explore data graphically

### Plot boxplots
ggpubr::ggboxplot(data = antlers,
          y = "mass",
          x = "diet",
          fill = "diet")

### Plot histograms
ggpubr::gghistogram(data = antlers,
          x = "mass",
          title = "All data")

#ggpubr::gghistogram(data = antlers,
 #         x = "mass",
          facet.by = "diet",
          fill = "diet",
          title = "Faceted by diet")

## Plot means with 95% confidence intervals
ggpubr::ggerrorplot(antlers,
  x = "diet",
  y = "mass",
  desc_stat = "mean_ci",
  add = "mean",
  ylim = c(400,900))


## 1-way ANOVA

### null model
model.null <- lm(mass ~ 1, data = antlers)

### model of interest
model.alt <- lm(mass ~ diet, data = antlers)

### compare models
anova(model.null, model.alt)

## Pairwise comparisons after 1-way ANOVA
### no corrections for multiple comparisons
pairwise.t.test(x = antlers$mass, g = antlers$diet,
      p.adjust.method = "none")

### Bonferonni correction
pairwise.t.test(x = antlers$mass, g = antlers$diet,
      p.adjust.method = "bonferroni")

## Tukey test

### re-fit model with aov()
model.alt.aov <- aov(mass ~ diet, data = antlers)

### TukeyHSD() on model from aov()
TukeyHSD(model.alt.aov)

### Plot effect sizes
# plotTukeysHSD(TukeyHSD(model.alt.aov))

## End(Not run)

brouwern/compbio4all documentation built on Dec. 19, 2021, 11:47 a.m.