A Lecture by Lecture Summary of Where We Are
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Date |
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Topic |
4th Edition |
5th Edition |
|
1/14 |
1 |
Research Plans, Experiments and other terminology |
Supp: Kuehl Chap 1 |
KNNL 15.1-15.4 Supp: Kuehl Chap 1 |
|
1/16 |
2 |
Basic Principles of Design |
NWNK 16.2, 16.3 Supp: Kuehl Chap 1 |
KNNL 15.3 |
|
1/18 |
3 |
Basic Principles of Design |
NWNK 16.2, 16.3 Supp: Kuehl Chap 1 |
KNNL 15.3 |
| 1/23 | 4 |
Complete and incomplete blocks Nested and split plot designs |
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| 1/25 | 5 |
Latin Squares Sample size |
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| 1/30 | 6 |
Picking Sample Sizes for t-tests |
Supp: Kuehl 1.7 NWNK 4.7 |
Supp: Kuehl 1.7 KNNL 4.7 |
| 2/1 | 7 |
Regression with Categorical Predictors Equivalence of Regression Models |
NWNK 11 |
KNNL 8.3-8.7 |
| 2/4 | 8 |
The One-Way Completely Randomized Design Parametrizing the Model |
NWNK 16.6-16.8 NWNK 16.10-16.11 |
KNNL 16.3, 16.7, 16.8 |
| 2/6 | 9 |
Fitting the Model Checking Model Assumptions |
NWNK 16.7 NWNK 18.1-18.6 |
KNNL 16.4-16.5 KNNL 18.1-18.6 |
| 2/8 | 10 |
The ANOVA Table F-test for Equal Means Inference for 1 mean |
NWNK 16.8 NWNK 16.9 read 16.10-16.11 |
KNNL 16.5, 16.6 |
| 2/11 | 11 |
Analysis of Factor Effects Contrasts and Orthogonality |
17.1-17.3 |
17.1-17.3 |
| 2/13 | 12 |
Single Degree of Freedom Tests |
17.3 |
|
| 2/15 | 13 |
Polynomial Effects for Quantitative Factors Lack of Fit of Linear Model |
17.9 |
17.9 |
| 2/18 | 14 | Multiple Comparisons |
17.4-17.7 |
17.4-17.7 |
| 2/20 | 15 | FDR | ||
| 2/22 | 16 |
Design for oneway ANOVA selecting levels determining sample size |
16.8,26.4 |
16.10, 16.11 17.8 |
| 2/25 | 17 |
ANCOVA - example |
25.1-25.3 |
22.1 |
| 2/27 | 18 |
more ANCOVA |
25.1-25.3 |
22.2-22.3 |
| 2/29 | 19 | ANCOVA to control for a variable | ||
| 3/3 | 20 |
2 - Factor ANOVA Models |
19.1-19.3 |
19.1,19.5 |
| 3/5 | 21 |
2 - Factor ANOVA - Parameters 2 - Factor ANOVA Table |
19.1-19.3 19.4 - 19.6 |
19.2,19.3 19.4, 19.6 |
| 3/7 | 22 |
2-Factor ANOVA example balanced and unbalanced |
19, 20, 22 |
19.7-19.10 |
| 3/17 | 23 |
contrasts of factor means |
20.3, 20.4,22.3 |
19.8,23.3 |
| 3/19 | 24 |
Multifactor ANOVA ExampleRandom Effects Models |
23 24.1 class handouts |
23.3, 25.1 class handouts |
| 3/21 | 25 |
Estimating Fixed Effects using OLS and GLS Estimating Variance Components using |
24.1 class handouts |
25.1 class handouts |
| 3/24 | 26 |
Estimating Variance Components using MLE, REML |
class handouts |
class handouts |
| 3/26 | 27 |
BLUPS, shrinkage |
class handouts |
class handouts |
| 3/28 | 28 |
tests of fixed and random effects Satterthwaite and Kenward Rogers approximate df and t (F) tests. |
Class handout |
Class handout |
| 3/31 | 29 |
Wald and LR tests One-Way Random Effects Model SAS GLM and Mixed - balanced |
Class handout |
Class handout |
| 4/2 | 30 |
One-Way Random Effects Model SAS GLM and Mixed - unbalanced, F<1.0 |
Class handout |
Class handout |
| 4/4 | 31 |
2-way balanced ANOVA with Random Effects - theory |
24.2-24.6 |
25.2-25.4 |
| 4/7 |
2-way MIXED effects ANOVA |
24.5 |
25.2-25.4 |
|
| 4/9 |
2-way designs with 0 variance components 3-way random effects designs |
24.6 |
25.6,25.7 |
|
| 4/11 |
Blocking and Randomized Complete Block Design |
26,27 |
21 |
|
| 4/14 | Nested Designs | 28 | 26 | |
| 4/16 |
split plot (blocks assigned at random) |
27.14,29.6 |
21.6, 27.6 |
|
| 4/18 |
split plot (sub-blocks within blocks) |
29.6 |
27.6 |
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| 4/23 |
|
30 |
28.3-28.6 |
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| 4/25 |
Replicated Latin Squares |
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|
|
| 4/28 |
Repeated Measures |
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|
|
| 4/30 |
Repeated Measures |
29, 30.7 |
27 | |
|
Confounding - Fractional Factorials, Incomplete blocks |
31 | 29 | ||
|
Response SurfaceDesigns |
32 | 30 | ||
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