map_to_weighting: creates a weighting function from a sampling frame

In mabafaba/hypegrammaR: A grammar of hypothesis test driven analysis

Description

creates a weighting function from a sampling frame

Usage

map_to_weighting(sampling.frame, data.stratum.column,
  sampling.frame.population.column = "population",
  sampling.frame.stratum.column = "stratum", data = NULL)

Arguments

data.stratum.column	data column name that holds the record's strata names
sampling.frame.population.column	sampling frame name of column holding population counts. defaults to "population"
sampling.frame.stratum.column	sampling frame name of column holding stratum names. defaults to "stratum". Stratum names must match exactly values in:
data	optional but recommended: you can provide an example data frame of data supposed to match the sampling frame to check if the provided variable names match and whether all strata in the data appear in the sampling frame.
sampling.frame.file	data frame containing the sampling frame. should contain columns "stratum" and "population", otherwise column names must be specified.

Value

returns a new function that takes a data frame as input returns a vector of weights corresponding to each row in the data frame.

Examples

## Not run: # load data and sampling frames:
mydata<-read.csv("mydata.csv")
mysamplingframe<-read.csv("mysamplingframe.csv")
# create weighting function:
weighting<-weighting_fun_from_samplingframe(sampling.frame = mysamplingframe,
                                 data.stratum.column = "strata_names",
                                 sampling.frame.population.column = "pop",
                                 sampling.frame.stratum.column = "strat_name")
# use weighting function:
mydata$weights<-weighting(mydata)

# this also works on subsets of the data:
mydata_subset<-mydata[1:100,]
subset_weights<- weighting(mydata)
## End(Not run)

mabafaba/hypegrammaR documentation built on Oct. 2, 2019, 11:33 a.m.