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MIXED ANOVA

MIXED ANOVA

Sometimes you may wish to run a mixed ANOVA - an ANOVA with both between and within factors. Again, in R this is easy to do.

Imagine you have data from two groups (men and women) at two time points (week one, week ten). See the plot below.
Picture
Assuming that the men are on the left and women are on the right, you might hypothesize that men have greater scores at Week Ten as opposed to on Week One, whereas there was no difference between scores for women at Week One and Week Ten. You could test this with a mixed ANOVA. 

Load the data HERE.

Use the following commands to run a mixed ANOVA:

my.data = read.table('mixedANOVAData.txt')
names(my.data) = c('Subject','Group','Time','RT')
my.data$Subject = factor(my.data$Subject)
my.data$Group = factor(my.data$Group)
my.data$Time = factor(my.data$Time)
myMixedANOVA = aov(RT ~ Group + Time +  Group*Time + Error(Subject / Time), data = my.data)
print(summary(myMixedANOVA))

boxplot(my.data$RT ~ my.data$Time*my.data$Group)

Note that in the ANOVA model Group is not included in the error term so it is treated as a Between subjects factor whereas Time is included in the error term so it is treated as a within subjects factor. Finally, there is an interaction term that specifies the interaction between the between (Group) and within (Time) subjects factors. You should see the output below:
Picture
The top portion is the result for the between subjects analysis of Group. The bottom portions are the results for the within subjects analysis of Time and the Group by Time interaction.
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245
    • EPHE 357
  • STATISTICS
    • BIOMEDICAL STATISTICS
    • RESOURCES
    • R TIPS
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops