# Estimation Methods for Causal Inference Based on Inverse Probability Weighting

## Documentation for package ‘causalweight’ version 1.1.2

- DESCRIPTION file.

## Help Pages

attrlateweight | Local average treatment effect estimation in multiple follow-up periods with outcome attrition based on inverse probability weighting
coffeeleaflet | Information leaflet on coffee production and environmental awareness of high school / university students in Bulgaria
coupon | Data on daily spending and coupon receipt (selective subsample) This data set is a selective subsample of the data set "couponsretailer" which was constructed for illustrative purposes.
couponsretailer | Data on daily spending and coupon receipt A dataset containing information on the purchasing behavior of 1582 retail store customers across 32 coupon campaigns.
didweight | Difference-in-differences based on inverse probability weighting
dyntreatDML | Dynamic treatment effect evaluation with double machine learning
games | Sales of video games
identificationDML | Testing identification with double machine learning
india | India's National Health Insurance Program (RSBY)
ivnr | Instrument-based treatment evaluation under endogeneity and non-response bias
JC | Job Corps data
lateweight | Local average treatment effect estimation based on inverse probability weighting
medDML | Causal mediation analysis with double machine learning
medlateweight | Causal mediation analysis with instruments for treatment and mediator based on weighting
medweight | Causal mediation analysis based on inverse probability weighting with optional sample selection correction.
medweightcont | Causal mediation analysis with a continuous treatment based on weighting by the inverse of generalized propensity scores
RDDcovar | Sharp regression discontinuity design conditional on covariates
rkd | Swedish municipalities
swissexper | Correspondence test in Swiss apprenticeship market
treatDML | Binary or multiple discrete treatment effect evaluation with double machine learning
treatselDML | Binary or multiple treatment effect evaluation with double machine learning under sample selection/outcome attrition
treatweight | Treatment evaluation based on inverse probability weighting with optional sample selection correction.
ubduration | Austrian unemployment duration data
wexpect | Wage expectations of students in Switzerland