Survey regression models

• Linear regression
• Logistic regression
• Cox regression
• Parametric survival regression
• Multinomial logistic regression
• Conditional logit regression
• Negative binomial regression
• Ordered logistic regression
• Probit regression
• Ordered probit regression
• Poisson regression
• 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

See multilevel models with survey data

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

Maximum pseudolikelihood estimation

• User-defined likelihoods
• Survey characteristics automatically handled

• 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

Factor variables

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

Marginal analysis

• 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

Watch Profile Plots and Interaction Plots in Stata

Contrasts

• 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

Watch Introduction to Contrasts in Stata: Oneway ANOVA tutorial.

Pairwise comparisons

• 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

Explore more about survey data analysis in Stata.