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survey (version 4.2-1)

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.

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Version

Install

install.packages('survey')

Monthly Downloads

77,056

Version

4.2-1

License

GPL-2 | GPL-3

Maintainer

Thomas Lumley

Last Published

May 3rd, 2023

Functions in survey (4.2-1)

Estimated weights for missing data

Household crowding

Lay out tables of survey statistics

Confidence intervals for regression parameters

US 2004 presidential election data at state or county level

Hadamard matrices

Calibration (GREG) estimators

dimnames.DBIsvydesign

Dimensions of survey designs

Small survey example

compressWeights

Compress replicate weight matrix

Experimental: Construct non-response weights

Standardised predictions (predictive margins) for regression models.

Sample of obstetric hospitals

Cholesterol data from a US survey

Two-stage sample from MU284

Association between leprosy and BCG vaccination

Calibration metrics

open.DBIsvydesign

Open and close DBI connections

Paley-type Hadamard matrices

Deprecated implementation of quantiles

Wald test for a term in a regression model

Take a stratified sample

Raking of replicate weight design

Post-stratify a survey

Distribution of quadratic forms

Survival in cardiac arrest

Salamander mating data set from McCullagh and Nelder (1989)

poisson_sampling

Specify Poisson sampling design

subset.survey.design

Subset of survey

Options for the survey package

Compute variance from replicates

Pseudo-Rsquareds

Specify survey design with replicate weights

Summary statistics for sample surveys

Sandwich variance estimator for glms

Confidence intervals for proportions

Computations for survey variances

Contingency tables for survey data

Test of fit to known probabilities

Survey statistics on subsets

Survey-weighted Cox models.

Survey-weighted generalised linear models.

Cronbach's alpha

Linear and nonlinearconstrasts of survey statistics

Conditioning plots of survey data

Two-stage least-squares for instrumental variable regression

Histograms and boxplots

Cumulative Distribution Function

Factor analysis in complex surveys (experimental).

Survey sample analysis.

Loglinear models

Proportional odds and related models

Sampling-weighted principal component analysis

Maximum pseudolikelihood estimation in complex surveys

Plots for survey data

Probability-weighted nonlinear least squares

Cohen's kappa for agreement

Compare survival distributions

Predictive marginal means

Scatterplot smoothing and density estimation

Variance estimation for multistage surveys

Design-based t-test

Score tests in survey regression models

Fit accelerated failure models to survey data

Estimate survival function.

Quantile-quantile plots for survey data

withPV.survey.design

Analyse plausible values in surveys

with.svyimputationList

Analyse multiple imputations

Direct standardization within domains

Quantiles under complex sampling.

Design-based rank tests

update.survey.design

Add variables to a survey design

One variable from the Youth Risk Behaviors Survey, 2015.

Compute variances by replicate weighting

Ratio estimation

Crossed effects and other sparse correlations

Two-phase designs

weights.survey.design

Survey design weights

Trim sampling weights

Extract standard errors

Wrappers for specifying PPS designs

Compute replicate weights

Convert a survey design to use replicate weights

Compute survey bootstrap weights

Student performance in California schools

barplot.svystat

Barplots and Dotplots

Update to the new survey design format

Model comparison for glms.

Package sample and population size data