--- title: "Testing for Multiple Comparisons and the Fisher Assumptions" author: "Randi Garcia" output: html_document: theme: cerulean highlight: pygments css: ../lab.css toc: true toc_float: true --- ```{r global-options, include=FALSE} knitr::opts_chunk$set(eval = FALSE) library(dplyr) library(lattice) library(ggplot2) library(tidyr) library(mosaic) library(forcats) ``` ## SP/RM[2,1] ```{r} osmo <- read.csv("http://www.science.smith.edu/~rgarcia/sds290-S18/osmoregulation3.csv") ``` ```{r} osmo <- osmo %>% mutate(Worms = as.factor(Worms), Time = as.factor(Time), Species = as.factor(Species), Concentration = as.factor(Concentration)) ``` ## Informal analyses Facet wrap for 3-way interaction plots ```{r} ggplot(osmo, aes(x = Time, y = Data, color = Species)) + geom_boxplot() + facet_wrap(~Concentration) ``` ## Formal Analysis ANOVA ```{r} mod <- aov(Data ~ Time*Concentration*Species + Error(Worms) + Concentration*Species, data = osmo) summary(mod) ``` ## Adjusting for Multiple Comparisons ```{r} library(lsmeans) lsmeans(mod, pairwise ~ Time, adjust="tukey") ``` ## Testing Assumptions ```{r} library(dae) ggplot(osmo, aes(x = residuals(mod))) + geom_histogram() ggplot(osmo, aes(sample = residuals(mod))) + geom_qq() ggplot(osmo, aes(x = fitted(mod), y = residuals(mod))) + geom_point() + geom_hline(yintercept = 0, color = "red") ```