Package sample and population size data
Convert a survey design to use replicate weights
Model comparison for glms.
Student performance in California schools
Wrappers for specifying PPS designs
Extract standard errors
Update to the new survey design format
Barplots and Dotplots
Compute survey bootstrap weights
Compute replicate weights
Estimated weights for missing data
Small survey example
Confidence intervals for regression parameters
Household crowding
Open and close DBI connections
Paley-type Hadamard matrices
Take a stratified sample
Subset of survey
Sandwich variance estimator for glms
Computations for survey variances
Sample of obstetric hospitals
Calibration metrics
Options for the survey package
Histograms and boxplots
Cohen's kappa for agreement
Quantiles for sample surveys
Dimensions of survey designs
US 2004 presidential election data at state or county level
Cholesterol data from a US survey
Experimental: Construct non-response weights
Pseudo-Rsquareds
Raking of replicate weight design
Linear and nonlinearconstrasts of survey statistics
Lay out tables of survey statistics
Hadamard matrices
Standardised predictions (predictive margins) for regression models.
Two-stage sample from MU284
Wald test for a term in a regression model
Survival in cardiac arrest
Survey-weighted Cox models.
Survey sample analysis.
Conditioning plots of survey data
Estimate survival function.
Loglinear models
Sampling-weighted principal component analysis
Design-based rank tests
Analyse multiple imputations
Compute variances by replicate weighting
Predictive marginal means
Compare survival distributions
Maximum pseudolikelihood estimation in complex surveys
Scatterplot smoothing and density estimation
Direct standardization within domains
One variable from the Youth Risk Behaviors Survey, 2015.
Calibration (GREG) estimators
Compress replicate weight matrix
Distribution of quadratic forms
Post-stratify a survey
Compute variance from replicates
Specify survey design with replicate weights
Survey statistics on subsets
Cumulative Distribution Function
Proportional odds and related models
Plots for survey data
Ratio estimation
Summary statistics for sample surveys
Contingency tables for survey data
Confidence intervals for proportions
Factor analysis in complex surveys (experimental).
Survey-weighted generalised linear models.
Fit accelerated failure models to survey data
Design-based t-test
Variance estimation for multistage surveys
Trim sampling weights
Two-phase designs
Add variables to a survey design
Survey design weights