Survey regression models

• linear regressions
• logistic regressions
• Cox regression
  
• Parametric survival regression
  
• multinomial logistic regression
• Conditional logit regression
  
• negative binomial regression
• ordered logistic regression
• probit regressions
• ordered probit regressions
• Poisson regressions
• Structural equation modeling*
  
• censored and interval regression
• instrumental variables regression
• Heckman selection model
• Probit estimation with selection
• Nonlinear least squares
  
• Click here for a complete list

Variance and standard error estimates

• Taylor-series linearization (Huber/White/sandwich)
• balanced and repeated replications (BRR)
• Survey jackknife
  
• Bootstrap (with bootstrap replicate weights)*
• Successive difference replication (SDR)*
  

Sampling designs

• sampling (probability) weights
• stratification
• clustering
• multistage designs
• finite population correction in all stages
• Support for strata with one sampling unit
  

Features

• Poststratification
  
• design effects
• misspecification effects
• effects for linear combinations
• Coefficient of variation*
  
• estimate linear/nonlinear combinations of parameters
• hypotheses tests for survey data
• estimation with linear constraints
• Goodness of fit for logistic and probit estimators*
  
• Multiple imputation*

• Compare estimated means, intercepts, and slopes
  
• Compare marginal means, intercepts, and slopes
  
• Balanced and unbalanced data
  
• Nonlinear responses
  
• Multiple-comparison adjustments: Bonferroni, Šidák, Scheffé, Tukey HSD, Duncan, and Student-Newman-Keuls adjustments
  
• Group comparisons that are significant
  
• Graphs of pairwise comparisons

Summary statistics

• population and subpopulation means
• Population and subpopulation standard deviations
  
• 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

Maximum pseudo-likelihood estimation

• user-defined likelihoods
• survey characteristics automatically handled

• Automatically create indicators based on categorical variables
  
• Form interactions among discrete and continuous variables
  
• Include polynomial terms
  
• Perform contrasts of categories/levels
  

• Estimated marginal means
  
• Marginal and partial effects
  
• Average marginal and partial effects
  
• Least-squares means
  
• Predictive margins
  
• Adjusted predictions, means, and effects
  
• Contrasts of margins*
• Pairwise comparisons of margins*
• Profile plots*
• Graphs of margins and marginal effects*

• Analysis of main effects, simple effects, interaction effects, partial interaction effects, and nested effects
  
• Comparisons against reference groups, of adjacent levels, or against the grand mean
  
• Orthogonal polynomials
  
• Helmert contrasts
  
• Custom contrasts
  
• ANOVA-style tests
  
• Contrasts of nonlinear responses
  
• Multiple-comparison adjustments
  
• Balanced and unbalanced data
  
• Contrasts in odds-ratio metric
  
• Contrasts of means, intercepts, and slopes
  
• Graphs of contrasts
  
• Interaction plots