Skip to content
Skip to content
ScholarGate

Statistics — Page 49

Explore statistical methods, their assumptions, interpretation and limitations.

Research field

Method family

Point-Biserial Correlation

The point-biserial correlation coefficient (r_pb) measures the strength and direction of the linear association between one naturally dichotomous variable (coded 0/1) and one continuous variable. It is a special case of the Pearson product-...

Points of Attachment Index

The Points of Attachment Index (PAI) is a multidimensional measurement instrument, developed by Galen Trail, Matthew Robinson, Ronald Dick, and Andrew Gillentine in 2003, that captures the several distinct objects to which sport fans become...

Poisson Rate Regression

Poisson rate regression is the standard generalized linear model for analyzing event rates and counts, such as the number of deaths, hospitalizations, or new cases observed over a span of person-time. It models the logarithm of the expected...

Poisson Regression

Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the pre...

Policy Evaluation Causal Impact Analysis

Policy Evaluation Causal Impact Analysis applies the Bayesian structural time-series (BSTS) framework of Brodersen et al. (2015) to estimate the causal effect of a policy intervention on aggregate outcomes. By constructing a synthetic count...

Policy Evaluation Coarsened Exact Matching

Coarsened Exact Matching (CEM) is a quasi-experimental causal-inference technique that creates balanced treatment and control groups from observational data by temporarily coarsening covariates into bins, exactly matching units within those...

Policy Evaluation Counterfactual Impact Evaluation

Counterfactual Impact Evaluation (CIE) for policy assessment estimates the causal effect of a public policy or programme by comparing observed outcomes of participants against a rigorously constructed counterfactual — what would have happen...

Policy Evaluation Difference-in-Differences

Policy Evaluation DiD applies the difference-in-differences estimator specifically to assess the causal impact of government programs, regulations, or policy reforms. It compares outcome changes in a group exposed to the policy against a co...

Policy Evaluation Doubly Robust Estimation

Policy Evaluation Doubly Robust Estimation applies the doubly robust (DR) estimator to assess the causal effect of a public policy or programme. It combines a model of treatment assignment (propensity score) with a model of the outcome, and...

Policy Evaluation Entropy Balancing

Entropy balancing is a maximum-entropy reweighting method that assigns weights to control-group units so that their weighted covariate moments exactly match those of the treated group. Introduced by Hainmueller (2012), it provides exact bal...

Policy Evaluation Event Study Design

A policy evaluation event study design is a quasi-experimental approach that estimates causal effects of a policy by plotting treatment-period-by-period coefficients around a common event time. It extends difference-in-differences to visual...

Policy Evaluation Fuzzy Regression Discontinuity

Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates the causal effect of a policy when eligibility is determined by crossing a threshold on a continuous score, but actual take-up or compliance is imperfect. Developed formally by Hah...

Policy Evaluation Instrumental Variables

Instrumental Variables (IV) estimation for policy evaluation is a quasi-experimental technique that uses an exogenous instrument — a variable that shifts exposure to a policy but is otherwise unrelated to the outcome — to recover the causal...

Policy Evaluation Interrupted Time Series

Interrupted Time Series (ITS) for policy evaluation uses routinely collected aggregate time-series data to estimate the causal impact of a policy change. A segmented regression model splits the series at a known intervention date, estimatin...

Policy Evaluation Inverse Probability Weighting

Policy evaluation inverse probability weighting (IPW) uses estimated propensity scores to reweight observed units so that the weighted sample mimics a randomised experiment. Each unit is weighted by the inverse of its probability of receivi...

Policy Evaluation Marginal Structural Model

A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment...

Policy Evaluation Matching Estimator

The policy evaluation matching estimator estimates the causal effect of a program or policy on treated units by pairing each participant with one or more non-participants who share similar pre-treatment characteristics. Developed rigorously...

Policy Evaluation Panel Event Study

A panel event study is a quasi-experimental design that traces how an outcome evolves in periods before and after a policy event, using unit and time fixed effects to identify the causal effect. Widely used in economics and policy research,...

Policy Evaluation Placebo Test

A policy evaluation placebo test is a falsification check used in quasi-experimental research to validate a causal identification strategy. The researcher applies the same estimation method to a pseudo-treatment — a time period, group, or o...

Policy Evaluation Propensity Score Matching

Policy evaluation propensity score matching applies the propensity score framework — originally developed by Rosenbaum and Rubin (1983) and operationalized for program evaluation by Heckman et al. (1997) — to estimate the causal effect of a...

Policy Evaluation Propensity Score Weighting

Policy evaluation propensity score weighting applies inverse-probability weighting to observational data to estimate the causal effect of a policy program. By reweighting participants and non-participants so they resemble a target populatio...

Policy Evaluation Regression Discontinuity Design

Policy Evaluation Regression Discontinuity Design (Policy RDD) exploits a known eligibility threshold in a policy rule to estimate the causal effect of that policy on outcomes. Units just below the cutoff serve as a credible comparison grou...

Policy Evaluation Synthetic Control Method

The Synthetic Control Method (SCM) is a causal inference technique for evaluating the effect of a policy or intervention on a single treated unit — such as a region, country, or firm — by constructing a weighted combination of untreated com...

Political Budget Cycle Analysis

Political budget cycle analysis is an econometric framework for detecting whether incumbent governments manipulate fiscal policy — deficits, public spending, or taxes — in the run-up to elections to signal competence and win votes. Kenneth...