doSampling {samplingin}

Select Samples Given its Parameters

Description

Samples selection using systematic or PPS (Probability Proportional to Size) sampling method.

Usage

doSampling(
  pop,
  alloc,
  nsample,
  type,
  strata = NULL,
  ident = c("kdprov", "kdkab"),
  implicitby = NULL,
  method = "systematic",
  auxVar = NA,
  seed = 1,
  predetermined_rn = NULL,
  is_secondary = FALSE,
  verbose = TRUE
)

Arguments

pop

pop dataframe

alloc

allocation dataframe

nsample

variable on alloc df as allocation sample

type

type value for sample classification ('U' = Primary Samples, 'P' = Secondary Samples)

strata

strata variable, must available on both pop and alloc dataframe

ident

group by on allocation dataframe

implicitby

variable used as implicit stratification

method

method of sampling : "systematic" (the default), "srs" or "pps"

auxVar

auxiliary variable for pps sampling (method = "pps")

seed

seed

predetermined_rn

predetermined random number variable on allocation dataframe, the default value is NULL, random number will be generated randomly

is_secondary

if the value is TRUE, it will maintains existing primary samples and selects units that have not been selected as samples (FALSE as default)

verbose

verbose (TRUE as default)

Value

list of population data ("pop"), selected samples ("sampledf"), and details of sampling process ("details")

Examples

library(samplingin)
library(magrittr)
library(dplyr)

# Simple Random Sampling (SRS)
dtSampling_srs = doSampling(
   pop         = pop_dt
   , alloc     = alokasi_dt
   , nsample   = "n_primary"
   , type      = "U"
   , ident     = c("kdprov")
   , method    = "srs"
   , auxVar    = "Total"
   , seed      = 7892
)

# Population data with flag sample
pop_dt = dtSampling_srs$pop

# Selected Samples
dsampel = dtSampling_srs$sampledf

# Details of sampling process
rincian = dtSampling_srs$details

# PPS Sampling
dtSampling_pps = doSampling(
   pop         = pop_dt
   , alloc     = alokasi_dt
   , nsample   = "n_primary"
   , type      = "U"
   , ident     = c("kdprov")
   , method    = "pps"
   , auxVar    = "Total"
   , seed      = 1234
)

# Population data with flag sample
pop_dt = dtSampling_pps$pop

# Selected Samples
dsampel = dtSampling_pps$sampledf

# Details of sampling process
rincian = dtSampling_pps$details

# Systematic Sampling
dtSampling_sys = doSampling(
   pop         = pop_dt
   , alloc     = alokasi_dt
   , nsample   = "n_primary"
   , type      = "U"
   , ident     = c("kdprov")
   , method    = "systematic"
   , seed      = 4321
)

# Population data with flag sample
pop_dt = dtSampling_sys$pop

# Selected Samples
dsampel = dtSampling_sys$sampledf

# Details of sampling process
rincian = dtSampling_sys$details

# Systematic Sampling (Secondary Samples)

alokasi_dt_p = alokasi_dt %>%
   mutate(n_secondary = 2 * n_primary)

dtSampling_sys_p = doSampling(
   pop           = dtSampling_sys$pop
   , alloc       = alokasi_dt_p
   , nsample     = "n_secondary"
   , type        = "P"
   , ident       = c("kdprov")
   , method      = "systematic"
   , seed        = 6789
   , is_secondary = TRUE
)

# Population data with flag sample
pop_dt = dtSampling_sys_p$pop

# Selected Samples
dsampel = dtSampling_sys_p$sampledf

# Details of sampling process
rincian = dtSampling_sys_p$details

# Systematic Sampling with predetermined random number (predetermined_rn parameter)

alokasi_dt_rn = alokasi_dt %>% rowwise() %>% mutate(ar = runif(n(),0,1)) %>% ungroup

dtSampling_sys = doSampling(
   pop         = pop_dt
   , alloc     = alokasi_dt_rn
   , nsample   = "n_primary"
   , type      = "U"
   , ident     = c("kdprov")
   , method    = "systematic"
   , predetermined_rn = "ar"
   , seed      = 4321
)

# Population data with flag sample
pop_dt = dtSampling_sys$pop

# Selected Samples
dsampel = dtSampling_sys$sampledf

# Details of sampling process
rincian = dtSampling_sys$details