You can either give obtain_inclusion_probabilities() an declaration, as created by `declare_rs`

or you can specify the other arguments to describe a random sampling procedure.
This function is especially useful when units have different inclusion probabilties and the analyst plans to use inverse-probability weights.

obtain_inclusion_probabilities(declaration = NULL, N = NULL, strata_var = NULL, clust_var = NULL, n = NULL, prob = NULL, strata_n = NULL, strata_prob = NULL, simple = FALSE)

declaration | A random sampling declaration, created by |
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N | The number of units. N must be a positive integer. (required) |

strata_var | A vector of length N that indicates which stratum each unit belongs to. |

clust_var | A vector of length N that indicates which cluster each unit belongs to. |

n | Use for a design in which n units (or clusters) are sampled. In a stratified design, exactly n units in each stratum will be sampled. (optional) |

prob | Use for a design in which either floor(N*prob) or ceiling(N*prob) units (or clusters) are sampled. The probability of being sampled is exactly prob because with probability 1-prob, floor(N*prob) units (or clusters) will be sampled and with probability prob, ceiling(N*prob) units (or clusters) will be sampled. prob must be a real number between 0 and 1 inclusive. (optional) |

strata_n | Use for a design in which strata_n describes the number of units to sample within each stratum. |

strata_prob | 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. |

simple | logical, defaults to FALSE. If TRUE, simple random sampling is used. When simple = TRUE, please do not specify n or strata_n. |

# Draw a stratified random sample strata_var <- rep(c("A", "B","C"), times=c(50, 100, 200)) declaration <- declare_rs(strata_var = strata_var) observed_probabilities <- obtain_inclusion_probabilities(declaration = declaration) table(strata_var, observed_probabilities)#> observed_probabilities #> strata_var 0.5 #> A 50 #> B 100 #> C 200# Sometimes it is convenient to skip the declaration step observed_probabilities <- obtain_inclusion_probabilities(strata_var = strata_var) table(strata_var, observed_probabilities)#> observed_probabilities #> strata_var 0.5 #> A 50 #> B 100 #> C 200