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Screen units based on data availability

Source: R/screen_units.R
Screen.data.frame.Rd

Screens units (rows) 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 'data.frame'
Screen(
  x,
  id_col = NULL,
  unit_screen,
  dat_thresh = NULL,
  nonzero_thresh = NULL,
  Force = NULL,
  ...
)

Arguments

x

A data frame

id_col

Name of column of the data frame to be used as the identifier, e.g. normally this would be uCode for indicator data sets used in coins. This must be specified if Force is specified.

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 units 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.

...

arguments passed to or from other methods.

Value

Missing data stats and screened data as a list.

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.

See also vignette("screening").

Examples

# example data
iData <- ASEM_iData[40:51, c("uCode", "Research", "Pat", "CultServ", "CultGood")]

# screen to 75% data availability (by row)
l_scr <- Screen(iData, unit_screen = "byNA", dat_thresh = 0.75)

# summary of screening
head(l_scr$DataSummary)
#>    uCode N_missing N_zero N_miss_or_zero Dat_Avail Non_Zero LowData LowNonZero
#> 40   KOR         1      0              1      0.75        1   FALSE      FALSE
#> 41   LAO         3      0              3      0.25        1    TRUE      FALSE
#> 42   MYS         0      0              0      1.00        1   FALSE      FALSE
#> 43   MNG         0      0              0      1.00        1   FALSE      FALSE
#> 44   MMR         2      0              2      0.50        1    TRUE      FALSE
#> 45   NZL         0      0              0      1.00        1   FALSE      FALSE
#>    LowDatOrZeroFlag Included
#> 40            FALSE     TRUE
#> 41             TRUE    FALSE
#> 42            FALSE     TRUE
#> 43            FALSE     TRUE
#> 44             TRUE    FALSE
#> 45            FALSE     TRUE