Learn R Programming

⚠️There's a newer version (4.4-2) of this package.Take me there.

survey (version 3.17)

analysis of complex survey samples

Description

Summary statistics, generalised linear 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 designs. Graphics. Predictive margins by direct standardization. PPS sampling without replacement.

Copy Link

Version

Install

install.packages('survey')

Monthly Downloads

62,531

Version

3.17

License

GPL-2 | GPL-3

Maintainer

Thomas Lumley

Last Published

September 18th, 2009

Functions in survey (3.17)

nonresponse

Experimental: Construct non-response weights
SE

Extract standard errors
HR

Wrappers for specifying PPS designs
confint.svyglm

Confidence intervals for regression parameters
mu284

Two-stage sample from MU284
postStratify

Post-stratify a survey
svrVar

Compute variance from replicates
svyglm

Survey-weighted generalised linear models.
as.svydesign2

Update to the new survey design format
election

US 2004 presidential election data at state or county level
pchisqsum

Distribution of quadratic forms
as.svrepdesign

Convert a survey design to use replicate weights
dimnames.DBIsvydesign

Dimensions of survey designs
surveysummary

Summary statistics for sample surveys
estweights

Estimated weights for missing data
make.calfun

Calibration metrics
svrepdesign

Specify survey design with replicate weights
bootweights

Compute survey bootstrap weights
svyratio

Ratio estimation
svyciprop

Confidence intervals for proportions
update.survey.design

Add variables to a survey design
svyplot

Plots for survey data
rake

Raking of replicate weight design
svydesign

Survey sample analysis.
barplot.svystat

Barplots and Dotplots
svycontrast

Linear and nonlinearconstrasts of survey statistics
marginpred

Standardised predictions (predictive margins) for regression models.
weights.survey.design

Survey design weights
svyby

Survey statistics on subsets
brrweights

Compute replicate weights
svysmooth

Scatterplot smoothing and density estimation
with.svyimputationList

Analyse multiple imputations
svycoxph

Survey-weighted Cox models.
hadamard

Hadamard matrices
svykm

Estimate survival function.
open.DBIsvydesign

Open and close DBI connections
svyhist

Histograms and boxplots
svytable

Contingency tables for survey data
svyolr

Proportional odds and related models
withReplicates

Compute variances by replicate weighting
regTermTest

Wald test for a term in a regression model
ftable.svystat

Lay out tables of survey statistics
api

Student performance in California schools
svykappa

Cohen's kappa for agreement
svyrecvar

Variance estimation for multistage surveys
crowd

Household crowding
subset.survey.design

Subset of survey
as.fpc

Package sample and population size data
svyloglin

Loglinear models
compressWeights

Compress replicate weight matrix
paley

Paley-type Hadamard matrices
svycdf

Cumulative Distribution Function
surveyoptions

Options for the survey package
svymle

Maximum pseudolikelihood estimation in complex surveys
svy.varcoef

Sandwich variance estimator for glms
svycoplot

Conditioning plots of survey data
calibrate

Calibration (GREG) estimators
svyCprod

Computations for survey variances
svyquantile

Quantiles for sample surveys
svyttest

Design-based t-test
twophase

Two-phase designs
scd

Survival in cardiac arrest
fpc

Small survey example
hospital

Sample of obstetric hospitals