Mathematical Derivations and Implementation of Iterative Fitting Techniques with Computational Simulations.

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1: Background and Motivation

  • Newton-Raphson
  • Fisher Scoring
  • Iteratively Reweighted Least Squares (IRLS)


Intuition for Unifying Theory of GLMs with Derivations in Canonical and Non-Canonical Forms

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1: Background and Motivation


Efficiency & Statistical Power gains from Conditional Covariate Adjustment in A/B Testing & Randomized Trials

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1: Background and Motivation


Mathematically Rigorous derivations and Computational Simulations of FWER and FDR upper-bounding Procedures

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1: Background and Motivation


Getting Started

Specification of M-Bias, and an Introduction to the Challenges of Causal Discovery

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1. Background and Motivation


Hands-on Tutorials

Required Adjustment of A/B Tests via G-Methods in the Presence of Informative Censoring

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1: Background and Motivation


Hands-on Tutorials

Mathematical Derivation and Computational Simulation of the semi-parametric class of G-methods

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1: Introduction


Hands-on Tutorials

Computational Simulation of G-Methods under Model Misspecification

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1. Background and Motivation


Hands-on Tutorials

Case-Control Designs: Mathematical Derivations, Explanations, Computational Simulations, and Clearing up Misconceptions

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1: Background & Motivation


… Not another ‘hand-wavy’ CLT explanation… Let’s actually work through the math

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Background and Motivation

Andrew Rothman

Chief Data Scientist & Head of AI @ AIMatters | Harvard trained Statistician and Machine Learning Scientist | Interests in Statistical ML & Causal Inference

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