Inclusion Probabilities: Stratified Random Sampling

strata_rs_probabilities(strata = strata_var, prob = NULL, n = NULL,
strata_n = NULL, strata_prob = NULL, check_inputs = TRUE,
strata_var = NULL)

## Arguments

strata A vector of length N that indicates which stratum each unit belongs to. Can be a character, factor, or numeric vector. (required) Use for a design in which either floor(N_stratum*prob) or ceiling(N_stratum*prob) units are sampled within each stratum. The probability of being sampled is exactly prob because with probability 1-prob, floor(N_stratum*prob) units will be sampled and with probability prob, ceiling(N_stratum*prob) units will be sampled. prob must be a real number between 0 and 1 inclusive. (optional) Use for a design in which the scalar n describes the fixed number of units to sample in each stratum. This number does not vary across strata. Use for a design in which the numeric vector strata_n describes the number of units to sample within each stratum. Use for a design in which strata_prob describes the probability of being sampled within each stratum. Differs from prob in that the probability of being sampled can vary across strata. logical. Defaults to TRUE. deprecated

## Value

A vector length N indicating the probability of being sampled.

## Examples


strata <- rep(c("A", "B","C"), times = c(50, 100, 200))
probs <- strata_rs_probabilities(strata = strata)
table(strata, probs)#>       probs
#> strata 0.5
#>      A  50
#>      B 100
#>      C 200
probs <- strata_rs_probabilities(strata = strata, prob = .2)
table(strata, probs)#>       probs
#> strata 0.2
#>      A  50
#>      B 100
#>      C 200
probs <- strata_rs_probabilities(strata = strata, strata_prob = c(.1, .2, .3))
table(strata, probs)#>       probs
#> strata 0.1 0.2 0.3
#>      A  50   0   0
#>      B   0 100   0
#>      C   0   0 200
probs <- strata_rs_probabilities(strata = strata, strata_n = c(10, 40, 70))
table(strata, probs)#>       probs
#> strata 0.2 0.35 0.4
#>      A  50    0   0
#>      B   0    0 100
#>      C   0  200   0