Counterfactual and Causal Inference: Methods and Principles for Social Science Research

Statistical Methods of Causal Inference in Sports Science Research

Among the complex large quantity of sports phenomenon and sports issues, we need to discuss the causal relationship and essential rule in between. Mathematical statistics is one of the common and practical methods for causal inference. In order to better understand, select, and use mathematical statistic methods, and to avoid deviation of research result due to misuse or even abuse of statistic...

Uncertainty in Causal and Counterfactual Inference

We report 4 studies which show that there are systematic quantitative patterns in the way we reason with uncertainty during causal and counterfactual inference. Two specific type of uncertainty – uncertainty about facts and about causal relations – are explored, and used to model people’s causal inferences (Studies 1-3). We then consider the relationship between causal and counterfactual reason...

Social Mechanisms and Causal Inference

Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interp...

Matching Methods for Causal Inference

Causal Inference in Social Science An Elementary Introduction

This is a short and very elementary introduction to causal inference in social science applications targeted to machine learners. I illustrate the techniques described with examples chosen from the economics and marketing literature. 1 A motivating problem 1 Suppose you are given some data on ad spend and product sales in various 2 cities and are asked to predict how sales would respond to a co...