tbl_svy object.

A tbl_svy wraps a locally stored svydesign and adds methods for dplyr single-table verbs like mutate, group_by and summarise. Create a tbl_svy using as_survey_design.

Methods

tbl_df implements these methods from dplyr.

select or rename

Select or rename variables in a survey's dataset.

mutate or transmute

Modify and create variables in a survey's dataset.

group_by and summarise

Get descriptive statistics from survey.

Examples

library(survey)
library(dplyr)
data(api)
svy <- as_survey_design(apistrat, strata = stype, weights = pw)
svy
#> Stratified Independent Sampling design (with replacement)
#> Called via srvyr
#> Sampling variables:
#>   - ids: `1` 
#>   - strata: stype 
#>   - weights: pw 
#> Data variables: 
#>   - cds (chr), stype (fct), name (chr), sname (chr), snum (dbl), dname (chr),
#>     dnum (int), cname (chr), cnum (int), flag (int), pcttest (int), api00
#>     (int), api99 (int), target (int), growth (int), sch.wide (fct), comp.imp
#>     (fct), both (fct), awards (fct), meals (int), ell (int), yr.rnd (fct),
#>     mobility (int), acs.k3 (int), acs.46 (int), acs.core (int), pct.resp (int),
#>     not.hsg (int), hsg (int), some.col (int), col.grad (int), grad.sch (int),
#>     avg.ed (dbl), full (int), emer (int), enroll (int), api.stu (int), pw
#>     (dbl), fpc (dbl)

# Data manipulation verbs ---------------------------------------------------
filter(svy, pcttest > 95)
#> Stratified Independent Sampling design (with replacement)
#> Called via srvyr
#> Sampling variables:
#>   - ids: `1` 
#>   - strata: stype 
#>   - weights: pw 
#> Data variables: 
#>   - cds (chr), stype (fct), name (chr), sname (chr), snum (dbl), dname (chr),
#>     dnum (int), cname (chr), cnum (int), flag (int), pcttest (int), api00
#>     (int), api99 (int), target (int), growth (int), sch.wide (fct), comp.imp
#>     (fct), both (fct), awards (fct), meals (int), ell (int), yr.rnd (fct),
#>     mobility (int), acs.k3 (int), acs.46 (int), acs.core (int), pct.resp (int),
#>     not.hsg (int), hsg (int), some.col (int), col.grad (int), grad.sch (int),
#>     avg.ed (dbl), full (int), emer (int), enroll (int), api.stu (int), pw
#>     (dbl), fpc (dbl)
select(svy, starts_with("acs")) # variables used in survey design are automatically kept
#> Stratified Independent Sampling design (with replacement)
#> Called via srvyr
#> Sampling variables:
#>   - ids: `1` 
#>   - strata: stype 
#>   - weights: pw 
#> Data variables: 
#>   - acs.k3 (int), acs.46 (int), acs.core (int)
summarise(svy, col.grad = survey_mean(col.grad))
#> # A tibble: 1 × 2
#>   col.grad col.grad_se
#>      <dbl>       <dbl>
#> 1     19.9        1.06
mutate(svy, api_diff = api00 - api99)
#> Stratified Independent Sampling design (with replacement)
#> Called via srvyr
#> Sampling variables:
#>   - ids: `1` 
#>   - strata: stype 
#>   - weights: pw 
#> Data variables: 
#>   - cds (chr), stype (fct), name (chr), sname (chr), snum (dbl), dname (chr),
#>     dnum (int), cname (chr), cnum (int), flag (int), pcttest (int), api00
#>     (int), api99 (int), target (int), growth (int), sch.wide (fct), comp.imp
#>     (fct), both (fct), awards (fct), meals (int), ell (int), yr.rnd (fct),
#>     mobility (int), acs.k3 (int), acs.46 (int), acs.core (int), pct.resp (int),
#>     not.hsg (int), hsg (int), some.col (int), col.grad (int), grad.sch (int),
#>     avg.ed (dbl), full (int), emer (int), enroll (int), api.stu (int), pw
#>     (dbl), fpc (dbl), api_diff (int)

# Group by operations -------------------------------------------------------
# To calculate survey
svy_group <- group_by(svy, dname)

summarise(svy, col.grad = survey_mean(col.grad),
          api00 = survey_mean(api00, vartype = "ci"))
#> # A tibble: 1 × 5
#>   col.grad col.grad_se api00 api00_low api00_upp
#>      <dbl>       <dbl> <dbl>     <dbl>     <dbl>
#> 1     19.9        1.06  662.      643.      681.