Outcome types
Continuous
Interval-measured (interval-censored)
Binary
Ordinal
Complications addressed
Endogenous covariates
Sample selection
Nonrandom treatment assignment
Exogenous, based on observed variables
Endogenous, based partially on unobservables
Endogenous covariate types
Continuous
Binary
Ordinal
Interactions with exogenous covariates
Interactions with endogenous covariates
Quadratic and other polynomial forms
Treatment effects/Causal analysis
Binary or ordinal treatments
Average treatment effects (ATEs)
ATEs on the treated (ATETs)
ATEs on the untreated (ATEUs)
Potential-outcome means (POMs)
ATEs, ATETs, ATEUs, and POMs for
Full population
Subpopulations
Expected values for specific covariate values
“Treatment effects” are sometimes called “Causal effects”.
Watch Extended regression models (ERMs).
Inferences
Inference statistics
Expected means
Expected probabilities
Contrasts (differences) of expected means and probabilities (also called effects)
Marginal effects
Partial effects
Average structural function (ASF) means and effects
Average structural probability (ASP) means and effects
Estimates of statistics are available for:
Full population
Subpopulations
Expected values for specific covariate values
Censored and uncensored outcomes
Conditional analysis—specify values of all covariates
Population-averaged analysis—specify values of some covariates, or no covariates, and average (margin) over the rest
Inferences types
Tests against zero or any other value
Tests of equality
Contrasts
Pairwise comparisons
Confidence intervals for every statistic
Most inferences are performed via a tight integration with Stata’s marginal analysis facilities
Profile plots
Any inference statistic
Any statistic over subpopulations or subgroups (e.g, age groups or treatment levels)
Any statistic at multiple fixed levels of one or more covariates
Confidence intervals
Additional resource
