01:02:17
Instrumental Variables & Causal Inference from Observational Data: Key Concepts with Felix Elwert
56:00
Network Psychometrics & Exploratory Graph Analysis (EGA) with Hudson Golino
56:51
Intro to Mediation, Moderation, and Conditional Process Analysis with Amanda Montoya
01:06:29
Latent Class Analysis: Learn Key Concepts with Stephanie Lanza & Bethany Bray
01:00:07
Quantifying Sensitivity in Causal Inference with Kenneth Frank
57:49
Longitudinal Data Analysis Using R: An Introduction to Panel Data with Stephen Vaisey
01:00:38
Kenneth A. Bollen on Choosing Models for Longitudinal Data Analysis
01:07:54
Latent Growth Curve Modeling: An Introduction to Longitudinal Data with Dan McNeish
01:10:40
Statistical Genetics: Foundations for Genomic Data Analysis with Daniel Adkins
01:06:11
Bayesian Data Analysis: Methods in Advanced Models with Roy Levy
01:00:04
Structural Equation Modeling (SEM) with Rex B. Kline: An Introduction to Methods & Best Practices
35:54
Fully Bayesian Treatment of Missing Data with Paul Allison
01:19:27
Intro to Multilevel Models: Exploring Variance in Nested Data with Stephen Vaisey
56:17
Propensity Score Analysis: Get Started with Treatment Effect Estimation with Shenyang Guo
58:30
Bayesian Data Analysis: Get Started with Roy Levy
01:11:21
Introduction to Time Series Analysis: Practical Methods Explained with Daniel J. Henderson
56:43
Causal Inference with Machine Learning: An Introduction with Ashley Naimi
01:00:23
Introduction to Difference-in-Differences (DiD): Panel Data and Fixed Effects Models Explained
01:04:50
Introduction to Categorical Data Analysis: Understanding Nonlinear Effects with Trenton Mize
01:00:28
Introduction to Machine Learning Methods with Bruce Desmarais
01:06:35
A Short Introduction to R
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Since its founding in 2005, Statistical Horizons has established a reputation for providing outstanding training in statistics for researchers working in academia, business, non-profit organizations, and government.
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