KNNL

This note last modified September 1, 2024

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Faraway 8

Rao 14

Chapter 15

• 1
  • Observational studies
• 2
  • Study definitions
  • Randomization + Blocking
• 3
  • Types of experiments
    • Repeated measures - same person gets all treatments
• 4
  • Types of study designs
• 5
  • case study paired comparison experiment

Chapter 16

• 1
  • Intro to anova
• 2
  • regression vs anova
• 3
  • Single factor anova
  • cell means model
• 4
  • fitting an anova
• 5
  • anova table
  • calculations
• 6
  • F test
• 7
  • Factor effects model
  • Zero sum constraint
• 8
  • Regression approach (idk)
• 9
  • Randomization tests (no need for \(\epsilon\) to be normally distributed)
• 10
  • power analysis
• 11
  • More power analysis

Chapter 17

• 1
  • look idk something
• 2
  • estimated factor level means
• 3
  • testing factor level means
  • contrasts
• 4
  • simultaneous inference procedures
• 5
  • Tukey multiple testing
• 6
  • Scheffe multiple testing
• 7
  • Bonferroni multiple testing
  • Comparisons of all the multiple testing methods
• 8
  • Better power analysis

Chapter 18

• 1
  • Analyzing and visualizing ANOVAs
• 2
  • Hartley test???
• 3
  • Ch 18 is if the errors variances are non constantly distributed or are not normally distributed
• 4
  • weighted least squares for normally distributed but not same variance
• 5
  • various transformations depending on relation between errors and the cell level
  • Box cox
• 6
  • other departures
• 7
  • Non parametric F test
  • Kruskal Wallis test

Chapter 19

• 1
  • Intro to two sample
  • Why OFAAT is bad
• 2
  • Main effects
  • factor effects
  • additive studies
  • transformations of interactions
• 3
  • matrices
• 4
  • calculations
  • anova table
• 5
  • assumptions of two sample anova
• 6
  • F test for interactions
  • F test for main effects
  • Kimball for when you have different alphas? It’s some sort of correction
• 7
  • F test for interactions
• 8
  • Factor effects sans interactions
• 9
  • Factor effects with interactions
• 10
  • pooling sums of squares
• 11
  • pooling sums of squares

Chapter 21

• 1
  • Intro to blocking
• 2
  • Formula for blocking
• 3
  • do anova like two factor, no interaction effects.
• 4
  • Possible issues with blocking, assumptions
  • Tukey test for additivity
• 5
  • Analysis of treatment effects.
• 6
  • More than one block
• 7
  • More than one replicate per block
• 8
  • Mooore factors
• 9
  • Randomized complete block experiments

Chapter 22

• COOOOVARIANCE ANALYSIS

Chapter 25

• 1
  • Random anova
  • Intraclass correlation
  • point estimate / ci estimate of \(\sigma_{\mu}\)
• 2
  • anova model 3
  • a bit about multiple factor levels in anova model 2
• 3
  • how to do calcs for anova 3, anova 2
• 4
  • estimating effects in anova 3
  • multiple comparisons
  • marginal means
• 5
  • additive model (a3)
  • interaction effects (a3)
  • anova table
• 6
  • three factors? cri
• 7
  • unequal sample sizes