Take a stratified sample
This function takes a stratified sample without replacement from a data set.
Vector of stratum identifiers; will be coerced to character
named vector of stratum sample sizes, with names corresponding to the values of
vector of indices into
strata giving the sample
The "sampling" package has many more sampling algorithms.
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- anova.svyglm: 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: Update to the new survey design format
- barplot.svystat: Barplots and Dotplots
- bootweights: Compute survey bootstrap weights
- brrweights: Compute replicate weights
- calibrate: Calibration (GREG) estimators
- compressWeights: Compress replicate weight matrix
- confint.svyglm: Confidence intervals for regression parameters
- crowd: Household crowding
- dimnames.DBIsvydesign: 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: Lay out tables of survey statistics
- hadamard: Hadamard matrices
- hospital: Sample of obstetric hospitals
- HR: Wrappers for specifying PPS designs
- make.calfun: Calibration metrics
- marginpred: Standardised predictions (predictive margins) for regression...
- mu284: Two-stage sample from MU284
- nhanes: Cholesterol data from a US survey
- nonresponse: Experimental: Construct non-response weights
- open.DBIsvydesign: Open and close DBI connections
- paley: Paley-type Hadamard matrices
- pchisqsum: Distribution of quadratic forms
- postStratify: Post-stratify a survey
- rake: Raking of replicate weight design
- regTermTest: Wald test for a term in a regression model
- scd: Survival in cardiac arrest
- SE: Extract standard errors
- stratsample: Take a stratified sample
- subset.survey.design: Subset of survey
- surveyoptions: Options for the survey package
- surveysummary: Summary statistics for sample surveys
- svrepdesign: Specify survey design with replicate weights
- svrVar: Compute variance from replicates
- svyby: Survey statistics on subsets
- svycdf: Cumulative Distribution Function
- svychisq: Contingency tables for survey data
- svyciprop: Confidence intervals for proportions
- svycontrast: Linear and nonlinearconstrasts of survey statistics
- svycoplot: Conditioning plots of survey data
- svycoxph: Survey-weighted Cox models.
- svyCprod: Computations for survey variances
- svydesign: Survey sample analysis.
- svyfactanal: Factor analysis in complex surveys (experimental).
- svyglm: Survey-weighted generalised linear models.
- svyhist: Histograms and boxplots
- svykappa: Cohen's kappa for agreement
- svykm: Estimate survival function.
- svyloglin: Loglinear models
- svylogrank: Compare survival distributions
- svymle: Maximum pseudolikelihood estimation in complex surveys
- svyolr: Proportional odds and related models
- svyplot: Plots for survey data
- svyprcomp: Sampling-weighted principal component analysis
- svypredmeans: Predictive marginal means
- svyquantile: Quantiles for sample surveys
- svyranktest: Design-based rank tests
- svyratio: Ratio estimation
- svyrecvar: Variance estimation for multistage surveys
- svysmooth: Scatterplot smoothing and density estimation
- svystandardize: Direct standardization within domains
- svyttest: Design-based t-test
- svy.varcoef: Sandwich variance estimator for glms
- trimWeights: Trim sampling weights
- twophase: Two-phase designs
- update.survey.design: Add variables to a survey design
- weights.survey.design: Survey design weights
- withReplicates: Compute variances by replicate weighting
- with.svyimputationList: Analyse multiple imputations
- yrbs: One variable from the Youth Risk Behaviors Survey, 2015.