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
`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
`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
`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()` `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
`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.

Reference

All functions