Package index • survey

All functions

HR() ppsmat() ppscov(): Wrappers for specifying PPS designs
SE(): Extract standard errors
anova(<svyglm>) anova(<svycoxph>) AIC(<svyglm>) BIC(<svyglm>) extractAIC(<svyglm>) extractAIC(<svrepglm>): Model comparison for glms.
api: Student performance in California schools
as.fpc(): Package sample and population size data
as.svrepdesign(): Convert a survey design to use replicate weights
as.svydesign2() .svycheck(): Update to the new survey design format
barplot(<svystat>) barplot(<svrepstat>) barplot(<svyby>) dotchart(<svystat>) dotchart(<svrepstat>) dotchart(<svyby>): Barplots and Dotplots
bootweights() subbootweights() mrbweights(): Compute survey bootstrap weights
brrweights() jk1weights() jknweights(): Compute replicate weights
calibrate() grake() cal_names(): Calibration (GREG) estimators
compressWeights() as.matrix(<repweights_compressed>) as.vector(<repweights_compressed>): Compress replicate weight matrix
confint(<svyglm>): Confidence intervals for regression parameters
crowd: Household crowding
dim(<survey.design>) dim(<svyimputationList>) dimnames(<survey.design>) dimnames(<DBIsvydesign>) dimnames(<svyimputationList>): Dimensions of survey designs
election: US 2004 presidential election data at state or county level
estWeights(): Estimated weights for missing data
fpc: Small survey example
ftable(<svystat>) ftable(<svrepstat>) ftable(<svyby>): Lay out tables of survey statistics
hadamard(): Hadamard matrices
hospital: Sample of obstetric hospitals
make.calfun(): Calibration metrics
marginpred(): Standardised predictions (predictive margins) for regression models.
mu284: Two-stage sample from MU284
multiframe(): Dual-frame and multi-frame surveys
multiphase(): Multiphase sampling designs
myco: Association between leprosy and BCG vaccination
nhanes: Cholesterol data from a US survey
nonresponse() sparseCells() neighbours() joinCells() weights(<nonresponse>): Experimental: Construct non-response weights
oldsvyquantile(<survey.design>) oldsvyquantile(<svyrep.design>): Deprecated implementation of quantiles
open(<DBIsvydesign>) close(<DBIsvydesign>): Open and close DBI connections
paley() is.hadamard(): Paley-type Hadamard matrices
pchisqsum() pFsum(): Distribution of quadratic forms
phoneframes: Database of household expenses for two sampling frames
poisson_sampling(): Specify Poisson sampling design
postStratify(): Post-stratify a survey
psrsq(): Pseudo-Rsquareds
rake(): Raking of replicate weight design
regTermTest(): Wald test for a term in a regression model
reweight() plot(<dualframe_with_rewt>): Reweight (optimise) the weights on frames
salamander: Salamander mating data set from McCullagh and Nelder (1989)
scd: Survival in cardiac arrest
svysmoothArea(): Small area estimation via basic area level model
svysmoothUnit(): Smooth via basic unit level model
stratsample(): Take a stratified sample
subset(<survey.design>) subset(<svyrep.design>): Subset of survey
surveyoptions survey.lonely.psu survey.ultimate.cluster survey.adjust.domain.lonely survey.want.obsolete survey.drop.replicates survey.multicore survey.replicates.mse survey.use_rcpp: Options for the survey package
svymean(<survey.design>) svymean(<survey.design2>) svymean(<twophase>) svymean(<svyrep.design>) svyvar(<survey.design>) svyvar(<svyrep.design>) svytotal(<survey.design>) svytotal(<survey.design2>) svytotal(<twophase>) svytotal(<svyrep.design>) coef(<svystat>) coef(<svrepstat>) vcov(<svystat>) vcov(<svrepstat>) confint(<svystat>) confint(<svrepstat>) cv() deff() make.formula(): Summary statistics for sample surveys
svrVar(): Compute variance from replicates
svrepdesign() `degf<-`() image(<svyrep.design>): Specify survey design with replicate weights
svy.varcoef(): Sandwich variance estimator for glms
svyCprod() onestage(): Computations for survey variances
svyby() SE(<svyby>) deff(<svyby>) coef(<svyby>) confint(<svyby>) unwtd.count() svybys(): Survey statistics on subsets
svycdf() print(<svycdf>) plot(<svycdf>): Cumulative Distribution Function
svytable(<survey.design>) svytable(<svyrep.design>) svychisq(<survey.design>) svychisq(<svyrep.design>) summary(<svytable>) degf(): Contingency tables for survey data
svyciprop(): Confidence intervals for proportions
svycontrast(): Linear and nonlinearconstrasts of survey statistics
svycoplot(): Conditioning plots of survey data
svycoxph() predict(<svycoxph>) AIC(<svycoxph>): Survey-weighted Cox models.
svycralpha(): Cronbach's alpha
svydesign(): Survey sample analysis.
svyfactanal(): Factor analysis in complex surveys (experimental).
svyglm(<survey.design>) svyglm(<svyrep.design>) summary(<svyglm>) predict(<svyglm>) predict(<svrepglm>): Survey-weighted generalised linear models.
svygofchisq(): Test of fit to known probabilities
svyhist() svyboxplot(): Histograms and boxplots
svyivreg(): Two-stage least-squares for instrumental variable regression
svykappa(): Cohen's kappa for agreement
svykm() plot(<svykm>) lines(<svykm>) plot(<svykmlist>) quantile(<svykm>) confint(<svykm>): Estimate survival function.
svyloglin() update(<svyloglin>) anova(<svyloglin>) print(<anova.svyloglin>) coef(<svyloglin>): Loglinear models
svylogrank(): Compare survival distributions
svymle() summary(<svymle>): Maximum pseudolikelihood estimation in complex surveys
svynls(): Probability-weighted nonlinear least squares
svyolr() predict(<svyolr>): Proportional odds and related models
svyplot(): Plots for survey data
svyprcomp() biplot(<svyprcomp>): Sampling-weighted principal component analysis
svypredmeans(): Predictive marginal means
svyqqplot() svyqqmath(): Quantile-quantile plots for survey data
svyquantile(): Quantiles under complex sampling.
svyranktest(): Design-based rank tests
svyratio(<survey.design2>) svyratio(<svyrep.design>) svyratio(<twophase>) predict(<svyratio>) predict(<svyratio_separate>) SE(<svyratio>) coef(<svyratio>) confint(<svyratio>): Ratio estimation
svyrecvar(): Variance estimation for multistage surveys
svyscoretest(): Score tests in survey regression models
svysmooth() plot(<svysmooth>) lines(<svysmooth>) make.panel.svysmooth(): Scatterplot smoothing and density estimation
svystandardize(): Direct standardization within domains
svysurvreg(<survey.design>): Fit accelerated failure models to survey data
svyttest(): Design-based t-test
trimWeights(): Trim sampling weights
twophase() twophasevar() twophase2var(): Two-phase designs
update(<survey.design>) update(<twophase>) update(<svyrep.design>) update(<DBIsvydesign>): Add variables to a survey design
weights(<survey.design>) weights(<svyrep.design>) weights(<survey_fpc>): Survey design weights
with(<svyimputationList>) subset(<svyimputationList>): Analyse multiple imputations
withCrossval(): Crossvalidation using replicate weights
withPV(<survey.design>): Analyse plausible values in surveys
withReplicates() vcov(<svyrep.design>): Compute variances by replicate weighting
xdesign(): Crossed effects and other sparse correlations
yrbs: One variable from the Youth Risk Behaviors Survey, 2015.