  This paper serves as a literature review of methodology concerning the
(modern) causal inference methods to address the causal estimand with
observational/survey data that have been or will be used in social science
research. Mainly, this paper is divided into two parts: inference from
statistical estimand for the causal estimand, in which we reviewed the
assumptions for causal identification and the methodological strategies
addressing the problems if some of the assumptions are violated. We also
discuss the asymptotical analysis concerning the measure from the observational
data to the theoretical measure and replicate the deduction of the
efficient/doubly robust average treatment effect estimator, which is commonly
used in current social science analysis.
