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survey (version 3.31-2)

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

3.31-2

License

GPL-2 | GPL-3

Maintainer

Thomas Lumley

Last Published

September 23rd, 2016

Functions in survey (3.31-2)

compressWeights

Compress replicate weight matrix

Convert a survey design to use replicate weights

Compute survey bootstrap weights

Compute replicate weights

Calibration (GREG) estimators

Update to the new survey design format

Model comparison for glms.

Student performance in California schools

barplot.svystat

Barplots and Dotplots

Package sample and population size data

Confidence intervals for regression parameters

Wrappers for specifying PPS designs

dimnames.DBIsvydesign

Dimensions of survey designs

Small survey example

Estimated weights for missing data

Sample of obstetric hospitals

US 2004 presidential election data at state or county level

Household crowding

Lay out tables of survey statistics

Hadamard matrices

Post-stratify a survey

Two-stage sample from MU284

Distribution of quadratic forms

open.DBIsvydesign

Open and close DBI connections

Standardised predictions (predictive margins) for regression models.

Calibration metrics

Experimental: Construct non-response weights

Paley-type Hadamard matrices

Raking of replicate weight design

Cholesterol data from a US survey

Options for the survey package

Take a stratified sample

Extract standard errors

Wald test for a term in a regression model

Sandwich variance estimator for glms

Summary statistics for sample surveys

Survival in cardiac arrest

Compute variance from replicates

Survey statistics on subsets

subset.survey.design

Subset of survey

Confidence intervals for proportions

Conditioning plots of survey data

Survey-weighted generalised linear models.

Survey-weighted Cox models.

Contingency tables for survey data

Factor analysis in complex surveys (experimental).

Cumulative Distribution Function

Linear and nonlinearconstrasts of survey statistics

Computations for survey variances

Survey sample analysis.

Compare survival distributions

Maximum pseudolikelihood estimation in complex surveys

Plots for survey data

Proportional odds and related models

Estimate survival function.

Loglinear models

Predictive marginal means

Sampling-weighted principal component analysis

Histograms and boxplots

Cohen's kappa for agreement

Quantiles for sample surveys

Design-based rank tests

with.svyimputationList

Analyse multiple imputations

weights.survey.design

Survey design weights

Scatterplot smoothing and density estimation

Compute variances by replicate weighting

Direct standardization within domains

Variance estimation for multistage surveys

Ratio estimation

Two-phase designs

update.survey.design

Add variables to a survey design

Design-based t-test

Trim sampling weights