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雷达卡
This ebook is really good for beginner of Statistician, so detail, so clear...
contents
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Regression with Stata
Chapter 1 - Simple and Multiple Regression
Chapter Outline
1.0 Introduction
1.1 A First Regression Analysis
1.2 Examining Data
1.3 Simple linear regression
1.4 Multiple regression
1.5 Transforming variables
1.6 Summary
1.7 Self assessment
1.8 For more information
Regression with Stata
Chapter 2 - Regression Diagnostics
Chapter Outline
2.0 Regression Diagnostics
2.1 Unusual and Influential data
2.2 Checking Normality of Residuals
2.3 Checking Homoscedasticity
2.4 Checking for Multicollinearity
2.5 Checking Linearity
2.6 Model Specification
2.7 Issues of Independence
2.8 Summary
2.9 Self assessment
2.10 For more information
Regression with Stata
Chapter 3 - Regression with Categorical Predictors
Chapter Outline
3.0 Regression with Categorical Predictors
3.1 Regression with a 0/1 variable
3.2 Regression with a 1/2 variable
3.3 Regression with a 1/2/3 variable
3.4 Regression with multiple categorical predictors
3.5 Categorical predictor with interactions
3.6 Continuous and Categorical variables
3.7 Interactions of Continuous by 0/1 Categorical variables
3.8 Continuous and Categorical variables, interaction with 1/2/3 variable
3.9 Summary
3.10 Self assessment
3.11 For more information
Regression with Stata
Chapter 4 - Beyond OLS
Chapter Outline
4.1 Robust Regression Methods
4.1.1 Regression with Robust Standard Errors
4.1.2 Using the Cluster Option
4.1.3 Robust Regression
4.1.4 Quantile Regression
4.2 Constrained Linear Regression
4.3 Regression with Censored or Truncated Data
4.3.1 Regression with Censored Data
4.3.2 Regression with Truncated Data
4.4 Regression with Measurement Error
4.5 Multiple Equation Regression Models
4.5.1 Seemingly Unrelated Regression
4.5.2 Multivariate Regression
4.6 Summary
4.7 Self assessment
4.8 For more information
Regression with Stata
Chapter 5 - Additional coding systems for categorical variables in regression analysis
Chapter Outline
5.1 Simple Coding
5.2 Forward Difference Coding
5.3 Backward Difference Coding
5.4 Helmert Coding
5.5 Reverse Helmert Coding
5.6 Deviation Coding
5.7 Orthogonal Polynomial Coding
5.8 User-Defined Coding
5.9 Summary
Regression with Stata
Chapter 6: More on interactions of categorical variables
Draft version
This is a draft version of this chapter. Comments and suggestions to improve this draft are welcome.
Chapter outline
6.1. Analysis with two categorical variables
6.2. Simple effects
6.2.1 Analyzing simple effects using xi3 and regress
6.2.2 Coding of simple effects
6.3. Simple comparisons
6.3.1 Analyzing simple comparisons using xi3 and regress
6.3.2 Coding of simple comparisons
6.4. Partial interaction
6.4.1 Analyzing partial interactions using xi3 and regress
6.4.2 Coding of partial interactions
6.5. Interaction contrasts
6.5.1 Analyzing interaction contrasts using xi3 and regress
6.5.2 Coding of interaction contrasts
6.6. Computing adjusted means
6.6.1 Computing adjusted means via anova
6.6.1 Computing adjusted means via regress
6.7. More details on meaning of coefficients
6.8. Simple effects via dummy coding versus effect coding
6.8.1 Example 1. Simple effects of yr_rnd at levels of mealcat
6.8.2 Example 2. Simple effects of mealcat at levels of yr_rnd
Regression with Stata
Chapter 7: More on interactions of categorical and continuous variables
This is a draft version of this chapter. Comments and suggestions to improve this draft are welcome.
Chapter Outline
1. Continuous and Categorical Predictors without Interaction
2. Continuous and Categorical Predictors with Interaction
3. Show slopes for each group
3.1 Show slopes by performing separate analyses
3.2 Show slopes for each group from one analysis
4. Compare slopes across groups
5. Simple effects and simple comparisons of group, strategy 1
5.1 Simple effects and comparisons when meals is 1 sd below mean
5.2 Simple effects and comparisons when meals is at the mean
5.3 Simple effects and comparisons when meals is 1 sd above the mean
6. Simple effects and simple comparisons of group, strategy 2
6.1 Simple effects and comparisons when meals is 1 sd below mean
6.2 Simple effects and comparisons when meals is at the mean
6.3 Simple effects and comparisons when meals is 1 sd above mean
7. Interaction Comparison
8. More on predicted values
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