English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 5h 05m | 599 MB
Stata is agile, easy to use, and fast, with the ability to load and process up to 120,000 variables and over 20 billion observations. In this course, take a deeper dive into the popular statistics software. Instructor Franz Buscha explores advanced and specialized topics in Stata, from panel data modeling to interaction effects in regression models. Franz demonstrates several sophisticated data management functions and visualization techniques to complement the basic Stata operations that you may have already mastered. Plus learn about Monte Carlo simulations, count data analysis, survival analysis, and more.
Topics include:
- Formatting the display of variables
- Repeating commands by looping
- Visualization techniques, including drawing custom functions
- Interaction effects in regression models
- Panel data modeling
- Random numbers and simulation methods
- Count data modeling
- Survival analysis
Table of Contents
Introduction
1 Specialized statistics with Stata
2 What you should know
More on Data Management
3 Formatting the display of variables
4 Date and time variables
5 Repeating commands by looping over variables
6 Repeating commands by looping over numbers
7 Repeating commands by looping within loops
8 Accessing results saved from Stata commands
9 Challenge More on data management
10 Solution More on data management
More on Visualization Techniques
11 Changing the look of markers
12 Changing graph colors
13 Graphing by groups
14 Controlling legends
15 Adding text and textboxes
16 Sizing graphs
17 Combining graphs
18 How to use jitter
19 How to draw custom functions
20 Challenge More on visualization techniques
21 Solution More on visualization techniques
Interaction Effects in Regression Models
22 What is an interaction effect
23 How to use margins and marginsplot
24 Continuous polynomial interactions
25 Continuous by continuous interactions
26 Categorical by categorical interactions
27 Categorical by linear interactions
28 Challenge Interaction effects
29 Solution Interaction effects
Panel Data Modeling
30 Setting up panel data
31 Setting up panel data demo
32 Panel data descriptives
33 Panel data descriptives demo
34 Panel data dynamics
35 Panel data dynamics demo
36 Linear panel estimators
37 Linear panel estimators demo
38 Random or fixed effects
39 The Hausman test demo
40 Nonlinear panel data estimators
41 Nonlinear panel data estimators demo
42 Challenge Panel data modeling
43 Solution Panel data modeling
Random Numbers and Simulation
44 Drawing pseudorandom numbers
45 Data generating process (DGP)
46 Violating estimator assumptions
47 Monte Carlo simulation
48 Challenge Simulation
49 Solution Simulation
Count Modeling
50 Features of count data
51 Poisson model
52 Negative binomial models
53 Truncated models
54 Zero-inflated models
55 Challenge Count modeling
56 Solution Count modeling
Survival Analysis
57 What is survival data
58 Setting up survival data
59 Summary statistics
60 Nonparametric analysis
61 Cox proportional hazards model
62 Diagnostics for Cox models
63 Parametric proportional hazards models
64 Challenge Survival analysis
65 Solution Survival analysis
Conclusion
66 Next steps
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