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survey (version 3.37)

Analysis of Complex Survey Samples

Description

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Principal components, factor analysis.

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Version

Install

install.packages('survey')

Monthly Downloads

77,056

Version

3.37

License

GPL-2 | GPL-3

Maintainer

Thomas Lumley

Last Published

January 21st, 2020

Functions in survey (3.37)

Confidence intervals for regression parameters

Estimated weights for missing data

Compute replicate weights

Sample of obstetric hospitals

Calibration (GREG) estimators

Lay out tables of survey statistics

compressWeights

Compress replicate weight matrix

Calibration metrics

Survival in cardiac arrest

Wald test for a term in a regression model

Household crowding

Small survey example

open.DBIsvydesign

Open and close DBI connections

dimnames.DBIsvydesign

Dimensions of survey designs

Confidence intervals for proportions

Experimental: Construct non-response weights

Raking of replicate weight design

Cholesterol data from a US survey

Contingency tables for survey data

Survey-weighted generalised linear models.

Pseudo-Rsquareds

Hadamard matrices

Paley-type Hadamard matrices

Two-stage sample from MU284

Linear and nonlinearconstrasts of survey statistics

Standardised predictions (predictive margins) for regression models.

Conditioning plots of survey data

Options for the survey package

Maximum pseudolikelihood estimation in complex surveys

Quantiles for sample surveys

withPV.survey.design

Analyse plausible values in surveys

Design-based rank tests

with.svyimputationList

Analyse multiple imputations

Compare survival distributions

Histograms and boxplots

Direct standardization within domains

Scatterplot smoothing and density estimation

Fit accelerated failure models to survey data

Summary statistics for sample surveys

Design-based t-test

Survey statistics on subsets

US 2004 presidential election data at state or county level

Estimate survival function.

Cumulative Distribution Function

Loglinear models

Ratio estimation

subset.survey.design

Subset of survey

Take a stratified sample

Survey-weighted Cox models.

Distribution of quadratic forms

Variance estimation for multistage surveys

One variable from the Youth Risk Behaviors Survey, 2015.

Compute variances by replicate weighting

Cronbach's alpha

Compute variance from replicates

Factor analysis in complex surveys (experimental).

Proportional odds and related models

Trim sampling weights

Specify survey design with replicate weights

Computations for survey variances

Sandwich variance estimator for glms

Post-stratify a survey

Survey sample analysis.

Plots for survey data

Two-phase designs

Two-stage least-squares for instrumental variable regression

update.survey.design

Add variables to a survey design

Predictive marginal means

weights.survey.design

Survey design weights

Cohen's kappa for agreement

Sampling-weighted principal component analysis

Extract standard errors

Package sample and population size data

Wrappers for specifying PPS designs

Model comparison for glms.

Student performance in California schools

Compute survey bootstrap weights

barplot.svystat

Barplots and Dotplots

Update to the new survey design format

Convert a survey design to use replicate weights