Author
Franz Buscha
Released
9/19/2019- 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
Skill Level Advanced
Duration
Views
- [Franz] Stata is a general purpose statistical software that is fast, accurate, and easy to use. Stata can load and process up to 120,000 variables, 20 billion observations, and its multicore processing capability allows you to use up to 64 CPU cores to speed up your work. Today, Stata is one of the main statistical software programs on the market. In this course, we're going to cover advanced and specialized topics in Stata, such as Monte Carlo simulations, panel data analysis, survival analysis, count data analysis, and interaction effects in regression models. We will also look at advanced data management functions and advanced graphing techniques. Hi, I'm Franz Buscha and I've been using Stata for the last 20 years. Come and join me in my LinkedIn Learning course about advanced statistics with Stata.
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Introduction
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What you should know1m 23s
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1. More on Data Management
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Date and time variables6m 41s
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2. More on Visualization Techniques
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Changing the look of markers4m 50s
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Changing graph colors5m 31s
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Graphing by groups5m 45s
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Controlling legends5m 46s
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Adding text and textboxes6m 43s
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Sizing graphs4m 13s
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Combining graphs4m 50s
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How to use jitter4m 37s
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How to draw custom functions3m 19s
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3. Interaction Effects in Regression Models
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4. Panel Data Modeling
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Setting up panel data4m 13s
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Setting up panel data demo3m 40s
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Panel data descriptives3m 16s
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Panel data descriptives demo5m 52s
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Panel data dynamics3m 34s
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Panel data dynamics demo5m 52s
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Linear panel estimators5m 53s
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Linear panel estimators demo5m 15s
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Random or fixed effects2m 20s
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The Hausman test demo2m 14s
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5. Random Numbers and Simulation
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Drawing pseudorandom numbers5m 29s
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Monte Carlo simulation5m 34s
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Solution: Simulation4m 51s
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6. Count Modeling
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Features of count data5m 45s
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Poisson model7m 18s
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Negative binomial models6m 19s
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Truncated models6m 28s
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Zero-inflated models8m 28s
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Solution: Count modeling5m 3s
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7. Survival Analysis
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What is survival data?4m 11s
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Setting up survival data5m 43s
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Summary statistics5m 25s
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Nonparametric analysis6m 10s
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Diagnostics for Cox models5m 14s
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Solution: Survival analysis5m 10s
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Conclusion
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Next steps56s
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Video: Specialized statistics with Stata