Screen units based on data availability

Screens units based on a data availability threshold and presence of zeros. Units can be optionally "forced" to be included or excluded, making exceptions for the data availability threshold.

Usage

# S3 method for class 'purse'
Screen(
  x,
  dset,
  unit_screen,
  dat_thresh = NULL,
  nonzero_thresh = NULL,
  Force = NULL,
  write_to = NULL,
  ...
)

Arguments

x

A purse object

dset

The data set to be checked/screened

unit_screen

Specifies whether and how to screen units based on data availability or zero values.

If set to "byNA", screens units with data availability below dat_thresh
If set to "byzeros", screens units with non-zero values below nonzero_thresh
If set to "byNAandzeros", screens units based on either of the previous two criteria being true.

dat_thresh

A data availability threshold (>= 1 and <= 0) used for flagging low data and screening units if unit_screen != "none". Default 0.66.

nonzero_thresh

As dat_thresh but for non-zero values. Defaults to 0.05, i.e. it will flag any units with less than 5% non-zero values (equivalently more than 95% zero values).

Force

A data frame with any additional countries to force inclusion or exclusion. Required columns uCode (unit code(s)) and Include (logical: TRUE to include and FALSE to exclude). Specifications here override exclusion/inclusion based on data rules.

write_to

If specified, writes the aggregated data to .$Data[[write_to]]. Default write_to = "Screened".

...

arguments passed to or from other methods.

Value

An updated purse with coins screened and updated.

Details

The two main criteria of interest are NA values, and zeros. The summary table gives percentages of NA values for each unit, across indicators, and percentage zero values (as a percentage of non-NA values). Each unit is flagged as having low data or too many zeros based on thresholds.

Examples

# see vignette("screening") for an example.