Calculate rates

Calculate the rates for categorical (factor) or logical variables.

Usage

tab_rate(
  vr,
  pop,
  per = getOption("surveytable.rate_per"),
  drop_na = getOption("surveytable.drop_na"),
  max_levels = getOption("surveytable.max_levels"),
  csv = getOption("surveytable.csv")
)

Arguments

vr

variable to tabulate

pop

either a single number or a data.frame with columns named Level and Population. Level must exactly match the levels of vr. Population is the population for that level of vr.

per

calculate rate per this many items in the population

drop_na

drop missing values (NA)?

max_levels

a categorical variable can have at most this many levels. Used to avoid printing huge tables.

csv

name of a CSV file

Value

A list of tables or a single table.

See also

Other tables: tab(), tab_cross(), tab_subset_rate(), total(), total_rate()

Examples

set_survey(namcs2019sv)
#>                         Survey info {NAMCS 2019 PUF}                         
#> ┌───────────┬──────────────┬────────────────────────────────────────────────┐
#> │ Variables │ Observations │ Design                                         │
#> ├───────────┼──────────────┼────────────────────────────────────────────────┤
#> │        33 │        8,250 │ Stratified 1 - level Cluster Sampling design   │
#> │           │              │ (with replacement)                             │
#> │           │              │ With (398) clusters.                           │
#> │           │              │ namcs2019sv = survey::svydesign(ids = ~CPSUM,  │
#> │           │              │ strata = ~CSTRATM, weights = ~PATWT            │
#> │           │              │ , data = namcs2019sv_df)                       │
#> └───────────┴──────────────┴────────────────────────────────────────────────┘
#> 
# pop is a data frame
tab_rate("MSA", uspop2019$MSA)
#> Metropolitan Statistical Area Status of physician location (rate per 100 population) {NAMCS 2019 PUF}
#> ┌───────────────────────┬───────┬───────┬──────┬───────┬───────┐
#> │ Level                 │     n │  Rate │   SE │    LL │    UL │
#> ├───────────────────────┼───────┼───────┼──────┼───────┼───────┤
#> │ MSA (Metropolitan     │ 7,496 │ 351.2 │ 18.2 │ 317.2 │ 388.8 │
#> │ Statistical Area)     │       │       │      │       │       │
#> ├───────────────────────┼───────┼───────┼──────┼───────┼───────┤
#> │ Non-MSA               │   754 │ 136.7 │ 38.2 │  78.9 │ 236.8 │
#> └───────────────────────┴───────┴───────┴──────┴───────┴───────┘
#>   N = 8250.                                                     
#> 

# pop is a single number
tab_rate("MDDO", uspop2019$total)
#> * Rate based on the entire population.
#> Type of doctor (MD or DO) (rate per 100 population) {NAMCS 2019 PUF}
#> ┌───────────────────────┬───────┬───────┬────┬───────┬───────┐
#> │ Level                 │     n │  Rate │ SE │    LL │    UL │
#> ├───────────────────────┼───────┼───────┼────┼───────┼───────┤
#> │ M.D. - Doctor of      │ 7,498 │ 303.3 │ 15 │ 275.3 │ 334.1 │
#> │ Medicine              │       │       │    │       │       │
#> ├───────────────────────┼───────┼───────┼────┼───────┼───────┤
#> │ D.O. - Doctor of      │   752 │  17.4 │  2 │  13.8 │  21.9 │
#> │ Osteopathy            │       │       │    │       │       │
#> └───────────────────────┴───────┴───────┴────┴───────┴───────┘
#>   N = 8250.                                                   
#>