Gang Fang's Blog

Are random variables in causal inference equivalent to features in ML? My Answer: yes. My answer after reading ChatGPT: yes and no. They both represent aspects/elements of a data set or a model, but they are established under different contexts and serve different purposes. Random variables in CI are mainly used to discover causal relationships…

What is the “oracle” that serves as input to a constraint based search algorithm? Answer: the oracle typically refers to a black-box function that provides answers to queries made by the algorithm. Critique: this answer still doesn’t make much sense, I can create algorithms that can do anything with such an oracle. How does the…

A list of introductory papers by major contributors in causal inference A list of texts in causal inference

What does modeling really mean in statistical studies? Answer after reading: modeling is the process of representing a real-world phenomenon of interest with a mathematical model, usually simplified, in order to understand the phenomenon, answer questions and make predictions. The crucial steps include: identify the problem, collect data, select model, fit model (parameters) to data,…

Note 1: Mental framework of a SEM A structural equation model consists of two parts: the structural model and the measurement model, shown as below Can you describe a case study of SEM application? Case study: this is found in Structural equation modeling in medical research: a primer. Based on the general framework above, a…

What are the differences between SEM, Regression Analysis and ML? They all seem to estimate and predict the relationship between dependent variables and independent variables. Answer: They differ in multiple important aspects, such as scope, purpose, assumptions and output interpretation. Scope: SEM is a general modeling framework encompassing multiple multivariate techniques, while Regression Analysis is…

There is a section devoted to Structural Equation Models (SEMs) in Peter Spirtes’ paper, but he didn’t seem to explain what Structural Equation Modeling actually are. What is Structural Equation Modeling? My answer: Unlike Causal Bayesian Networks, which can be defined by their parts (i.e., G, P and the local directed Markov condition), Structural Equation…