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| #acl HlpLabGroup,TanenhausLabGroup:read,write,delete,revert,admin All:read #format wiki #language en #pragma section-numbers 4 |
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| Thursday, May 29 2008. | '''June 5 2008''' === Materials === * attachment:lexdecRT.R * attachment:BaayenETAL06.pdf |
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| === Notes on the readings === === Additional terminology === Feel free to add terms you want clarified in class: * * === Questions === * Q: Determining the significance of a coefficient: one-tailed or two-tailed t test? * A: It's a two-tailed test because we cannot a-priori assume which direction the coefficient will go. I guess if one had a really strong theoretical reason to assume one direction, you could do a one-tailed test (which is less conservative). == Suggested topics == If you have any material that you would like to cover that isn't included in the list below, please make note of it here. [[Anchor(assignments)]] |
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| Upload your solutions to this page by 10pm. |
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| || Baa08 || Section 6.7 (p. 260) || Exercise 1 || | || Baa08 || Section 6.7 (p. 260) || Exercise 1, 8 || |
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[[AttachList]] [[Anchor(Topics)]] == Topics == * More on outliers * detect outliers {{{boxplot()}}}, scatterplots {{{plot(), identify()}}}[[BR]] * dealing with outliers exclusion {{{subset()}}}[[BR]] robust regression (based on t-distribution): {{{tlm()}}} (in package {{{hatt}}})[[BR]] * Overly influential cases (can be, but don't have to be outliers) {{{lm.influence()}}}, also {{{library(Rcmdr)}}}[[BR]] * Collinearity: * tests: {{{vif(), kappa()}}}, summary of correlations between fixed effects in {{{lmer()}}} [[BR]] * countermeasures: * centering and/or standardizing {{{scale()}}}} [[BR]] * use of residuals {{{resid(lm(x1 ~ x2, data))}}} [[BR]] * principal component analysis (PCA) {{{princomp()}}} [[BR]] * Model evaluation: Where is the model off? * case-by-case: {{{residuals(), predict()}}}[[BR]] * based on predictor: {{{residuals()}}} against predictors, {{{calibrate()}}}[[BR]] * overall: {{{validate()}}}[[BR]] * Corrections: * correcting for clusters (violation of assumption of independence): {{{bootcov()}}}[[BR]] |
Session 2: Issues in linear regression
June 5 2008
Materials
- attachment:lexdecRT.R
- attachment:BaayenETAL06.pdf
Reading
G&H07 |
Chapter 4 (pp. 53-74) |
Linear regression: before and after fitting the model |
Baa08 |
Sections 6.2.2-6.2.4 (pp. 198-212) |
Collinearity, Model criticism, and Validation |
|
Section 6.4 (pp. 234-239) |
Regression with breakpoints |
Notes on the readings
Additional terminology
Feel free to add terms you want clarified in class:
Questions
- Q: Determining the significance of a coefficient: one-tailed or two-tailed t test?
- A: It's a two-tailed test because we cannot a-priori assume which direction the coefficient will go. I guess if one had a really strong theoretical reason
to assume one direction, you could do a one-tailed test (which is less conservative).
Suggested topics
If you have any material that you would like to cover that isn't included in the list below, please make note of it here.
Assignments
Upload your solutions to this page by 10pm.
G&H07 |
Section 4.9 (p.76) |
Exercise 4 |
Baa08 |
Section 6.7 (p. 260) |
Exercise 1, 8 |
In addition to the book problems, we will distribute a data set from the ongoing ngrams project.