Replication and blocking

Experimental Design in R

Joanne Xiong

Data Scientist

Replication

Must repeat an experiment to fully assess variability
If we only conduct a drug efficacy experiment on one person, how can we properly generalize those results? (We can't!)

library(dplyr)
mtcars %>%
    count(cyl)

    cyl  n
1   4     11
2   6      7
3   8     14

Blocking

Helps control variability by making treatment groups more alike
Inside of groups, differences will be minimal. Across groups, differences will be larger
One example is blocking treatment groups by sex

Boxplots

# Boxplot of MPG by Car Cylinders
ggplot(mtcars, aes(x=as.factor(cyl), 
                   y=mpg)) + 
  geom_boxplot(fill="slateblue", 
               alpha=0.2) + 
  xlab("cyl")

alt text

Functions for modeling

Linear models
```
lm(formula, data, na.action,...)
```
One-way ANOVA model
```
aov(formula, data = NULL, ...)
```
Nested ANOVA model
```
anova(object,...)
```

Let's practice!

Experimental Design in R