Regression Diagnostic Series: Qualitative applications in the social sciences / John Fox
Series: QUANTITATIVE APPLICATIONS IN THE SOCIAL SCIENCESPublication details: New Delhi, A sage University Paper, 1991.Description: 92 p. : ill. ; 21 cmISBN:- 080393971x
- 22 519.536 FOX
Item type | Current library | Call number | Copy number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
Book Open Access | Engineering Library | 519.536 FOX 1 (Browse shelf(Opens below)) | 1 | Available | BUML23111929 |
Table of Contents
I. Introduction
2. Linear least-squares regression
The regression model
Least-squares estimation
Statistical inference for regression coefficients
The general linear model
3. Collinearity
Collinearity and variation inflation Coping with Collinearity: No quick fix
4. Outfying and Influential data
Measuring leverage: hat-values
Detecting outliers: studentized residuals
Measuring influence: Cook's distance and other diagnostics
Numerical cutoffs for diagnostics statistics subsets of observation: partial-regression
Should unusual data be discarded
5. Non-distributed errors
Normal quintile-comparison plot of residuals
Histograms of residuals
Correcting asymmetry by transformation
6. Nonconstant error variation
Detecting Nonconstant error variance
Correcting Nonconstant error variance
7. Nonlinearity
Residual and partial-residual plots
Transformations for linearity
8 Discrete data
Testing for nonlinearity
Testing for nonconstant error variance
9. Maximum-likelihood methods, score tests, and constructed variables
Box-cox transformation of y
Box-Tidwell transformation of the xs
Nonconstant error variance revised
10. Recommendations
Computing diagnostics
Further reading
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