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survey (version 2.8-1)

analysis of complex survey samples

Description

Summary statistics, generalised linear models, and general maximum pseudolikelihood estimation for stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification and raking.

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Install

install.packages('survey')

Monthly Downloads

77,056

Version

2.8-1

License

LGPL

Maintainer

Thomas Lumley

Last Published

March 20th, 2024

Functions in survey (2.8-1)

Computations for survey variances

Maximum pseudolikelihood estimation in complex surveys

Summary statistics for sample surveys

subset.survey.design

Subset of survey

Specify survey design with replicate weights

Compute variances by replicate weighting

Survey-weighted generalised linear models.

Survey sample analysis.

Wald test for a term in a regression model

Contingency tables for survey data

Compute replicate weights

Lay out tables of survey statistics

Hadamard matrices

Survey-weighted generalised linear models.

Convert a survey design to use replicate weights

Sandwich variance estimator for glms

Household crowding

Compute variance from replicates

Post-stratify a survey

compressWeights

Compress replicate weight matrix

update.survey.design

Add variables to a survey design

Raking of replicate weight design

Extract standard errors

Plots for survey data

Experimental: Construct non-response weights

Ratio estimation

weights.survey.design

Survey design weights

Student performance in California schools

Quantiles for sample surveys

Survey statistics on subsets

Small survey example

Survival in cardiac arrest

Sample of obstetric hospitals