Blog Post – Shuhan (Alice) Ai

Bayesian Methods Research Project: Can Community Service Foster Social Agency Among STEM Students?

Bayesian

R

This post shares my STATS C216 final project, where I used Bayesian regression models to examine whether community service participation during college is associated with…

Shuhan (Alice) Ai

Bayesian Methods Part 5: Multilevel Models and Partial Pooling

Bayesian

R

Multilevel Models

Part 4 led us into Bayesian regression with MCMC. We used rstanarm to fit logistic, probit, and ordered models, and the main lesson was computational: once the posterior is…

Shuhan (Alice) Ai

Bayesian Methods Part 4: Regression with rstanarm — From Logistic to Ordered Models

Bayesian

R

Part 1 through Part 3 we worked with one simple model the whole way: the Beta-Binomial. It was a friendly place to start because everything had a clean formula. The…

Shuhan (Alice) Ai

Bayesian Methods Part 3: From Prior to Posterior — Conjugacy, Prediction, and Credible Intervals

Bayesian

R

Part 1 of this series argued that Frequentist error rates can be misleading once the data are in hand. Part 2 dealt with where priors come from — both subjective histogram…

Shuhan (Alice) Ai

Bayesian Methods Part 2: Specifying Prior Distributions and the Road to Posterior Inference

Bayesian

R

In Part 1, we saw that Frequentist error rates can be misleading once data are observed, and that the likelihood function lets data speak directly about which parameter…

Shuhan (Alice) Ai

Bayesian Methods Part 1: An Introduction to Bayesian and Likelihood Thinking

Bayesian

R

Have you ever made a decision and thought, “there’s a 5% chance I’m wrong”? In Frequentist statistics, that 5% error rate is calculated before we see the data. But once…

Shuhan (Alice) Ai

SCM Part 4: Variation Analysis and Causal Fairness Analysis

Causal Inference

How do we know whether a disparity between two groups is caused by direct discrimination, indirect systemic factors, or simply reflects demographic differences? Traditional…

Shuhan (Alice) Ai

Machine Learning Methods: Diffusion Models in ML and Generative Processes Through Iterative Denoising

Python

ML

In our previous tutorial, we explored Transformers and how machines learn to understand language. Now we’re stepping into one of the most fascinating areas of modern AI…

Shuhan (Alice) Ai

SCM Part 3: Counterfactuals, the Art of Asking ‘What If?’

Causal Inference

In the previous post, we explored the identification problem — learning how to compute \(P(y \mid do(x))\) from observational data using the back-door criterion, front-door…

Shuhan (Alice) Ai

Machine Learning Methods: From RNNs to Transformers, How Machines Learn to Read

Python

ML

In our previous tutorial, we explored gradient descent and regularization. Now we’re going to introduce one of the most exciting frontiers: teaching machines to understand…

Shuhan (Alice) Ai

SCM Part 2: From Back-door to Do-Calculus

Causal Inference

In the previous post, we explored the foundations of Structural Causal Models (SCMs) and how they allow us to formalize causal relationships. We learned that SCMs provide…

Shuhan (Alice) Ai

Structural Causal Models (SCM) Part 1: Pearl’s Causal Hierarchy and Causality Identification

Causal Inference

In the previous post, we’ve learnt the foundations of Directed Acyclic Graphs (DAGs) and Structural Causal Models (SCMs). This tutorial builds on those foundations with a…

Shuhan (Alice) Ai

Machine Learning Methods: Gradient Descent & Regularization

Python

ML

In our previous tutorial, we explored the fundamentals of linear and logistic regression. Now we’ll dive deeper into the math that powers modern machine learning: gradient…

Shuhan (Alice) Ai

Machine Learning Methods: Regression & Prediction

R

ML

Machine learning begins with a simple yet profound idea: predicting one thing from another. This chapter explores how we can build increasingly sophisticated models…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 10: Longitudinal Network Analysis

R

SNA

So far in this tutorial series, we’ve explored various aspects of social network analysis using cross-sectional data—networks captured at a single point in time. However…

Shuhan (Alice) Ai

Predicting STEM Undergraduates’ Intentions to Pursue Scientific Research Careers

Kernel Density

C++

R

ML

This document presents the results and R analyses for the STATS 202A final project

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 9: ERGM for Valued Networks

R

SNA

Welcome to Part 9 of the Social Network Analysis R Tutorial series. In our previous tutorials, we’ve been working exclusively with binary networks, where edges either exist…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 8: Triad Census Models

R

SNA

In this tutorial, we’ll explore triadic structures in social network and their role in understanding social relationships. We’ll learn how to use triad census models within…

Shuhan (Alice) Ai

Web Scraping in R: An Introduction Tutorial

R

Web scraping is the process of automatically extracting data from websites. In data analysis and research, we often need to collect data from online sources that don’t…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 7: Tapered ERGM Modeling, Social Balance and Transitivity, and MCMC Diagnostics

R

SNA

Welcome to Part 7 of our Social Network Analysis R Tutorial series! In our previous tutorial (Part 6), we explored the theoretical foundations of ERGMs, understanding the…

Shuhan (Alice) Ai

A Practical Machine Learning Guide in R

R

ML

Machine learning (ML) has become an increasingly valuable tool in educational research, offering powerful methods to predict student outcomes and identify key factors…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 6: ERGM Inference, Simulation, and Diagnostics

SNA

In this post, we’ll continue to explore the theoretical foundations of ERGM estimation, the computational methods used to fit these models, and the diagnostic tools for…

Shuhan (Alice) Ai

Calling C from R: A Performance Tutorial

R

C++

In data analysis and statistical computing, R is an excellent language for its expressiveness and extensive statistical libraries. However, R can be slow for certain…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 5: Hands-On ERGM Analysis

R

SNA

Welcome to Part 5 of our Social Network Analysis tutorial! In this hands-on session, we’ll work through three real-world examples of network modeling using ERGM.

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 4: Introduction to Network Models and ERGM

R

SNA

Welcome to Part 4 of our Social Network Analysis tutorial series! In this post, we’ll dive into the theoretical foundations of statistical network models and introduce the…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 3: Computing Social Network Statistics (Descriptive Analysis & Degree Distribution Modeling)

R

SNA

In the previous tutorial, we explored the mathematical foundations of network statistics, learning about degree, centrality, diameter, and more. Now it’s time to get our…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 2: Mathematical and Statistical Foundations

SNA

Have you ever wondered how to quantify the “importance” of a person in a social network (like the following graph, which family is the most powerful one among Renaissance…

Shuhan (Alice) Ai

Real-World Practice with Kernel Density and Regression Diagnostics

R

Kernel Density

Welcome to this advanced tutorial on kernel density estimation! This guide builds on the foundational kernel concepts from the previous blog post where we covered:

Shuhan (Alice) Ai

Introduction to Kernel Density Estimation and Rejection Sampling

R

Kernel Density

This tutorial introduces kernel density estimation and rejection sampling using Los Angeles housing price data. These methods are fundamental for exploratory data analysis…

Shuhan (Alice) Ai

Social Network Analysis R Tutorial Part 1: Basic Visualization

R

SNA

Ever wondered how to map friendships, track protein interactions, or visualize who’s connected to whom in Renaissance Florence? This tutorial will walk you through the…

Shuhan (Alice) Ai

Survival Analysis R Tutorial

R

Survival Analysis

This tutorial provides R example for survival analysis using PhD dissertation defense timing as the primary example.

Shuhan (Alice) Ai

What is Survival Analysis?

R

Survival Analysis

This post will introduce survival analysis and its application in higher education research.

Shuhan (Alice) Ai

How to code Race?

R

Critical Quant

This post will show several ways of race coding in quantitative social science research.

Shuhan (Alice) Ai

Causal Inference in Network Data: A Tutorial

SNA

Causal Inference

This is a tutorial for the causal inference with network data.

Yingshi Huang, Shuhan (Alice) Ai, Kayla Teng, Detao Ma

Difference-in-Differences (DID) and Regression Discontinuity Design (RDD)

R

Causal Inference

This tutorial focuses on two widely-used quasi-experimental methods: Difference-in-Differences (DID) and Regression Discontinuity Design (RDD).

Shuhan (Alice) Ai

Weighting Methods for Causal Inference

R

Causal Inference

In previous posts, we’ve explored the Potential Outcomes framework and matching methods for causal inference. Today, we’ll dive deeper into propensity score methods, which…

Shuhan (Alice) Ai

Matching Methods for Causal Inference

R

Causal Inference

Observational data rarely cooperate with our causal questions because treatment groups differ systematically from controls, confounding threatens validity, and randomization…

Shuhan (Alice) Ai

Causal Inference: An Introduction for Directed Acyclic Graphs (DAGs) and Structural Causal Models (SCM)

R

Causal Inference

Directed Acyclic Graphs (DAGs) and Structural Causal Models (SCMs) are complementary frameworks for thinking about causality.

Shuhan (Alice) Ai

Causal Inference: An Introduction for Potential Outcomes Framework

R

Causal Inference

This post provides a introduction to the Potential Outcomes Framework (also known as the Neyman-Rubin Causal Model) for causal inference.

Shuhan (Alice) Ai

Welcome to My Blog

A space for sharing research and reflections.

Shuhan (Alice) Ai