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In this course, you will :
- From panel data modelling to interaction effects in regression models, this course delves into advanced and specialised Stata topics.
- demonstrates a number of sophisticated data management functions and visualisation techniques to supplement the basic Stata operations you may already be familiar with.
- Discover Monte Carlo simulations, count data analysis, survival analysis, and other topics.
Syllabus :
1. More on Data Management
- Formatting the display of variables
- Date and time variables
- Repeating commands by looping over variables
- Repeating commands by looping over numbers
- Repeating commands by looping within loops
- Accessing results saved from Stata commands
2. More on Visualization Techniques
- Changing the look of markers
- Changing graph colors
- Graphing by groups
- Controlling legends
- Adding text and textboxes
- Sizing graphs
- Combining graphs
- How to use jitter
- How to draw custom functions
3. Interaction Effects in Regression Models
- What is an interaction effect?
- How to use margins and marginsplot
- Continuous polynomial interactions
- Continuous by continuous interactions
- Categorical by categorical interactions
- Categorical by linear interactions
4. Panel Data Modeling
- Setting up panel data
- Setting up panel data demo
- Panel data descriptives
- Panel data descriptives demo
- Panel data dynamics
- Panel data dynamics demo
- Linear panel estimators
- Linear panel estimators demo
- Random or fixed effects
- The Hausman test demo
- Nonlinear panel data estimators
- Nonlinear panel data estimators demo
5. Random Numbers and Simulation
- Drawing pseudorandom numbers
- Data generating process (DGP)
- Violating estimator assumptions
- Monte Carlo simulation
6. Count Modeling
- Features of count data
- Poisson model
- Negative binomial models
- Truncated models
- Zero-inflated models
7. Survival Analysis
- What is survival data?
- Setting up survival data
- Summary statistics
- Nonparametric analysis
- Cox proportional hazards model
- Diagnostics for Cox models
- Parametric proportional hazards models
