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IGTC01DA - Advanced and Specialized Statistics with Stata (EN)
01 - Introduction
02 - What you should know (1:23)
01 - Specialized statistics with Stata (0:57)
02 - 1. More on Data Management
02 - Date and time variables (6:41)
01 - Formatting the display of variables (5:56)
03 - Repeating commands by looping over variables (5:02)
04 - Repeating commands by looping over numbers (5:34)
05 - Repeating commands by looping within loops (4:43)
06 - Accessing results saved from Stata commands (7:12)
07 - Challenge More on data management (0:52)
08 - Solution More on data management (5:15)
03 - 2. More on Visualization Techniques
01 - Changing the look of markers (4:50)
02 - Changing graph colors (5:31)
03 - Graphing by groups (5:45)
04 - Controlling legends (5:46)
05 - Adding text and textboxes (6:43)
06 - Sizing graphs (4:13)
07 - Combining graphs (4:50)
08 - How to use jitter (4:37)
09 - How to draw custom functions (3:19)
10 - Challenge More on visualization techniques (0:55)
11 - Solution More on visualization techniques (3:55)
04 - 3. Interaction Effects in Regression Models
01 - What is an interaction effect (3:54)
02 - How to use margins and marginsplot (6:37)
03 - Continuous polynomial interactions (5:49)
04 - Continuous by continuous interactions (6:19)
05 - Categorical by categorical interactions (5:46)
06 - Categorical by linear interactions (5:37)
07 - Challenge Interaction effects (0:43)
08 - Solution Interaction effects (5:13)
05 - 4. Panel Data Modeling
02 - Setting up panel data demo (3:40)
01 - Setting up panel data (4:13)
03 - Panel data descriptives (3:16)
04 - Panel data descriptives demo (5:52)
05 - Panel data dynamics (3:34)
06 - Panel data dynamics demo (5:52)
07 - Linear panel estimators (5:53)
08 - Linear panel estimators demo (5:15)
09 - Random or fixed effects (2:20)
10 - The Hausman test demo (2:14)
11 - Nonlinear panel data estimators (2:27)
12 - Nonlinear panel data estimators demo (5:18)
13 - Challenge Panel data modeling (0:50)
14 - Solution Panel data modeling (6:48)
06 - 5. Random Numbers and Simulation
02 - Data generating process (DGP) (4:07)
01 - Drawing pseudorandom numbers (5:29)
03 - Violating estimator assumptions (5:28)
04 - Monte Carlo simulation (5:34)
05 - Challenge Simulation (0:47)
06 - Solution Simulation (4:51)
07 - 6. Count Modeling
02 - Poisson model (7:18)
01 - Features of count data (5:45)
03 - Negative binomial models (6:19)
04 - Truncated models (6:28)
05 - Zero-inflated models (8:28)
06 - Challenge Count modeling (0:45)
07 - Solution Count modeling (5:03)
08 - 7. Survival Analysis
01 - What is survival data (4:11)
02 - Setting up survival data (5:43)
03 - Summary statistics (5:26)
04 - Nonparametric analysis (6:10)
05 - Cox proportional hazards model (6:59)
06 - Diagnostics for Cox models (5:14)
07 - Parametric proportional hazards models (7:37)
08 - Challenge Survival analysis (0:43)
09 - Solution Survival analysis (5:11)
09 - Conclusion
01 - Next steps (0:57)
Ex_Files_Adv_Specialized_Statistics_Stata
Ex_Files_Adv_Specialized_Statistics_Stata
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02 - Poisson model
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