Канал: Practical Propensity Score Analysis

Identification and Estimation of Confirmatory Factor Analysis Models

Identification and Estimation of Confirmatory Factor Analysis Models

Introduction to Latent Class Analysis with Example in R

Introduction to Latent Class Analysis with Example in R

Testing metric versus scalar invariance with categorical indicators using Mplus

Testing metric versus scalar invariance with categorical indicators using Mplus

Automated Invariance Testing with Mplus

Automated Invariance Testing with Mplus

Sensitivity analysis for structural equation modeling using Mplus

Sensitivity analysis for structural equation modeling using Mplus

Sensitivity analysis for structural equation modeling (SEM)

Sensitivity analysis for structural equation modeling (SEM)

Analysis of heterogeneity of treatment effects with causal forests using the grf package in R

Analysis of heterogeneity of treatment effects with causal forests using the grf package in R

Path analysis with Mplus - Model Identification and Default Settings

Path analysis with Mplus - Model Identification and Default Settings

Neural networks to estimate propensity scores

Neural networks to estimate propensity scores

Overview of Propensity Score Estimation

Overview of Propensity Score Estimation

Overview of Quasi-experimental designs

Overview of Quasi-experimental designs

Overview of propensity score analysis

Overview of propensity score analysis

Estimation of average treatment effect of a continuous treatment with inverse probability weights

Estimation of average treatment effect of a continuous treatment with inverse probability weights

Evaluation of covariate balance of continuous treatment doses using inverse probability weighting

Evaluation of covariate balance of continuous treatment doses using inverse probability weighting

Inverse Probability Weighting for Continuous Treatment Doses

Inverse Probability Weighting for Continuous Treatment Doses

How to estimate the generalized propensity score and the dose response function

How to estimate the generalized propensity score and the dose response function

How to estimate generalized propensity scores for multiple treatment versions using R

How to estimate generalized propensity scores for multiple treatment versions using R

How to estimate treatment effects with differences-in-differences and fixed effects models

How to estimate treatment effects with differences-in-differences and fixed effects models

Inverse Probability Weighting for Time-Varying Treatments

Inverse Probability Weighting for Time-Varying Treatments

Optimal Full Matching on the Propensity Score using the MatchIt package in R

Optimal Full Matching on the Propensity Score using the MatchIt package in R

One-to-many matching with a genetic algorithm with the Matching package in R

One-to-many matching with a genetic algorithm with the Matching package in R

Variable ratio greedy propensity score matching with Matching Package in R

Variable ratio greedy propensity score matching with Matching Package in R

One-to-one greedy propensity score matching with the MatchIt package in R

One-to-one greedy propensity score matching with the MatchIt package in R

Marginal Mean Weighting Through Stratification to Estimate the Average Treatment Effect with R

Marginal Mean Weighting Through Stratification to Estimate the Average Treatment Effect with R

Propensity Score Stratification in R with the MatchIt and survey packages

Propensity Score Stratification in R with the MatchIt and survey packages

Doubly Robust Estimation with Propensity Score Weighting in R with the survey package

Doubly Robust Estimation with Propensity Score Weighting in R with the survey package

How to estimate a treatment effect with propensity score weights in R with the survey package

How to estimate a treatment effect with propensity score weights in R with the survey package

How to evaluate covariate balance with propensity score weights in R with the twang package

How to evaluate covariate balance with propensity score weights in R with the twang package

How to calculate propensity score weights in R

How to calculate propensity score weights in R

Generalized Boosted Modeling to Estimate Propensity Scores in R with the twang package

Generalized Boosted Modeling to Estimate Propensity Scores in R with the twang package

Classification trees and random forests to estimate propensity scores in R with the party package

Classification trees and random forests to estimate propensity scores in R with the party package

Logistic regression to estimate propensity scores in R

Logistic regression to estimate propensity scores in R

Multiple Imputation of Missing Data Prior to Propensity Score Estimation in R with the Mice

Multiple Imputation of Missing Data Prior to Propensity Score Estimation in R with the Mice

How to Run a Regression Analysis Using R and RStudio

How to Run a Regression Analysis Using R and RStudio