IIRF Online > Finance & Accounting > Economics > Stata > The STATA OMNIBUS: Regression and Modelling with STATA
The STATA OMNIBUS: Regression and Modelling with STATA by Udemy
4 COURSES IN 1! Includes introduction to Linear and Non-Linear Regression, Regression Modelling and STATA. Updated Freq.
Course Highlights
- The theory behind linear and non-linear regression analysis.
- To be at ease with regression terminology.
- The assumptions and requirements of Ordinary Least Squares (OLS) regression.
- To comfortably interpret and analyse regression output from Ordinary Least Squares.
- To learn and understand how Logit and Probit models work.
- To learn tips and tricks around Non-Linear Regression analysis.
- Practical examples in Stata
- Tips for building regression models
- An introduction to Stata
- Data manipulation in Stata
- Data visualisation in Stata
- Data analysis in Stata
- Regression modelling in Stata
- Simulation in Stata
- Survival analysis
- Count Data analysis
- Categorical Data analysis
- Panel Data Analysis
- Epidemiology
- Instrumental Variables
- Power Analysis
- Difference-in-Differences
Skills you will learn!
Curriculum
1 Topic
Introduction
26 Topics
What is Easy Statistics: Linear Regression?
What is Linear Regression?
Learning Outcomes
Who is this Course for?
Pre-requisites
Using Stata
What is Regression Analysis?
What is Linear Regression?
Why is Regression Analysis Useful?
What Types of Regression Analysis Exist?
Explaining Regression
Lines of Best Fit
Causality vs Correlation
What is Ordinary Least Squares?
Ordinary Least Squares Visual 1
Ordinary Least Squares Visual 2
Sum of Squares
Best Linear Unbiased Estimator
The Gauss-Markov Assumptions
Homoskedasticity
No Perfect Collinearity
Linear in Parameters
Zero Conditional Mean
How to Test and Correct for Endogeneity
The Gauss-Markov Assumptions Recap
Stata - Applied Examples
22 Topics
What is Easy Statistics: Non-Linear Regression?
What is Non-Linear Regression?
What are the main learning outcomes?
Who is this course for?
Prerequisites
Using Stata
What is Non-Linear Regression analysis?
How does Non-Linear Regression work?
Why is Non-Linear Regression analysis useful?
Types of Non-Linear Regression models
Maximum Likelihood
Linear Probability Model
The Logit and Probit Transformation
Latent Variables
What are Marginal Effects?
Dummy Explanatory Variables
Multiple Non-Linear Regression
Goodness-of-Fit
A note about Logit Coefficients
Tips for Logit and Probit Regression
Back to the Linear Probability Model?
Stata - Applied Logit and Probit Examples
14 Topics
Introduction
Regression Modelling - Don't Rush It
Functional Form - How to Model Non-Linear Relationships in a Linear Regression
Functional Form - Stata Examples
Interaction Effects - How to Use and Interpret Interaction Effects
Interaction Effects - Stata Examples
Using Time - Exploring Dynamics Relationships with Time Information
Using Time - Stata Examples
Categorical Explanatory Variables - How to Code Use and Interpret them
Categorical Explanatory Variables - Stata Examples
Dealing with Multicollinearity - Excluding and Transforming Collinear Variables
Dealing with Multicollinearity - Stata Examples
Dealing with Missing Values - Seeing the Unseeable
Dealing with Missing Values - Stata Examples
7 Topics
Introduction
The Stata Interface
Using Help in Stata
Command Syntax
.do and .ado Files
Log Files
Importing Data
7 Topics
Viewing Raw Data
Describing and Summarizing
Missing Values
Tabulating and Tables
Numerical Distributional Analysis
Using Weights
The New Table Command (Stata 17)
14 Topics
Recoding an Existing Variable
Creating New Variables Replacing Old Variables
Naming and Labelling Variables
Extensions to Generate
Indicator Variables
Keep and Drop Data/Variables
Saving Data
Converting String Data
Combining Data
Using Macro's and Loop's Effectively
Accessing Stored Information
Multiple Loops
Date Variables
Subscripting over Groups
15 Topics
Graphing in Stata
Bar Graphs and Dot Charts
Graphing Distributions
Pie Charts
Scatterplots and Lines of Best Fit
Graphing Custom Functions
Contour Plots (and Interaction Effects)
Jitter Data in Scatterplots
Sunflower Plots
Combining Graphs
Changing Graph Sizes
Graphing by Groups
Changing Graph Colours
Adding Text to Graphs
Scatterplots with Categories
4 Topics
Association Between Two Categorical Variables
Testing Means
Bivariate Correlation
Analysis of Variance (ANOVA)
11 Topics
Ordinary Least Squares (OLS) Regression
Factor Variables in OLS Regression
Diagnostic Statistics for OLS Regression
Log Dependent Variables and Interaction Effects in OLS Regression
Hypothesis Testing in OLS Regression
Presenting Estimates from OLS Regression
Standardizing Regression Estimates
Graphing Regression Estimates
Oaxaca Decomposition Analysis
Mixed Models: Random Intercepts and Random Coefficients
Constrained Linear Regression
3 Topics
Binary Choice Models (Logit/Probit Regression)
Diagnostics and Interpretation of Logit and Probit Regression
Ordered and Multinomial Choice Models
1 Topic
Fractional Logit Beta Regression and Zero-inflated Beta Regression
4 Topics
Random Numbers
Data Generating Process
Simulating a Violation of Statistical Assumptions
Monte Carlo Simulation
5 Topics
Features of Count Data
Poisson Regression
Negative Binomial Regression
Truncated and Censored Count Regression
Hurdle Count Regression
7 Topics
What is Survival Analysis?
Setting up Survival Data
Descriptive Statistics in Survival Data
Non-parametric Survival Analysis
Cox Proportional Hazard's Model
Diagnostics for Cox Models
Parametric Survival Analysis
6 Topics
Setting up Panel Data
Panel Data Descriptives
Lags and Leads
Linear Panel Estimators
The Hausman Test
Non-Linear Panel Estimators
3 Topics
Difference-in-Differences Estimation
Parellel Trend Assumption
Difference-in-Differences without Parallel Trends
4 Topics
Instrumental Variable Regression
Multiple Endogenous Variables
Non-linear Instrumental Variable Regression
Heckman Selection Models
5 Topics
Introduction and Rate Data
Cumulative Incidence Data
Case-Control Data
Case-Control Data with Multiple Exposure
Matched Case-Control Data
3 Topics
Power Analysis: Sample Size
Power Analysis: Power and Effect Size
Power Analysis: Simple Regression
4 Topics
Matrix Operations
Matrix Functions
Matrix Subscripting
Matrix Operations with Data
1 Topic
The Stata Practice Test
The STATA OMNIBUS: Regression and Modelling with STATA
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