Survey regression models
- Linear regression
- Logistic regression
- Multinomial logistic regression
- Negative binomial regression
- Ordered logistic regression
- Probit regression
- Ordered probit regression
- Poisson regression
- Censored and interval regression
- Instrumental variables regression
- Heckman selection model
- Probit estimation with selection
Variance and standard error estimates
- Taylor-series linearization (Huber/White/sandwich)
- Balanced and repeated replications (BRR)
- Survey jackknife
Features
- Design effects
- Misspecification effects
- Effects for linear combinations
- Estimate linear/nonlinear combinations of parameters
- Hypotheses tests for survey data
- Poststratification
- Estimation with linear constraints
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Summary statistics
- Population and subpopulation means
- Population and subpopulation proportions
- Population and subpopulation ratios
- Population and subpopulation totals
- Provide full covariance estimates across subpopulations
Summary tables
- Two-way contingency tables with tests of independence
- One-way tables
- Table describing the sampling design of survey data
Estimators that support linear constraints
Sampling designs
- Sampling (probability) weights
- Stratification
- Clustering
- Multistage designs
- Finite population correction in all stages
Marginal effects
- Marginal effects and elasticities
- Standard errors and confidence intervals
- Computed at means or specified covariate values
- Computed for any predicted statistic
Maximum pseudolikelihood estimation
- User-defined likelihoods
- Survey characteristics automatically handled
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