Complete a panel dataset with an audit trail

complete_panel() expands a panel dataset so that every observed panel unit appears in every observed time period. Newly created unit-time cells are flagged with audit columns, and substantive variables are left missing.

Usage

complete_panel(data, id, time)

Arguments

data

A data frame or tibble.

id

Unquoted column name identifying the panel unit, such as a person, firm, district, county, or country.

time

Unquoted column name identifying the time period, such as a year, month, quarter, or date.

Value

A tibble containing the completed panel grid. The returned data include the original columns plus the following audit columns:

panelbuild_original_row

Logical indicator for rows present in the original data.

panelbuild_completed_cell

Logical indicator for rows created by complete_panel().

panelbuild_audit_action

Character label describing whether a row was original or added during panel completion.

The returned tibble also includes attributes documenting the panel identifier, time variable, number of completed cells, and audit note.

Details

The function first audits the panel using audit_panel(). If duplicate unit-time cells are present, the function stops with an error. This is intentional: completing a panel with duplicate unit-time observations can produce ambiguous results.

complete_panel() does not impute outcomes, covariates, treatment variables, or any other substantive variables. It only creates the missing unit-time rows implied by the full unit-by-time grid. Newly created rows are flagged using audit columns.

See also

audit_panel(), missing_cells(), gap_summary(), duplicate_summary()

Examples

panel_unique <- example_panel |>
  dplyr::distinct(id, year, .keep_all = TRUE)

complete_panel(panel_unique, id = id, time = year)
#> # A tibble: 12 × 7
#>       id  year outcome treatment panelbuild_original_row panelbuild_completed_…¹
#>    <dbl> <dbl>   <dbl>     <dbl> <lgl>                   <lgl>                  
#>  1     1  2020      10         0 TRUE                    FALSE                  
#>  2     1  2021      12         1 TRUE                    FALSE                  
#>  3     1  2022      NA        NA FALSE                   TRUE                   
#>  4     1  2023      NA        NA FALSE                   TRUE                   
#>  5     2  2020      20         0 TRUE                    FALSE                  
#>  6     2  2021      NA        NA FALSE                   TRUE                   
#>  7     2  2022      25         1 TRUE                    FALSE                  
#>  8     2  2023      NA        NA FALSE                   TRUE                   
#>  9     3  2020      30         0 TRUE                    FALSE                  
#> 10     3  2021      31         0 TRUE                    FALSE                  
#> 11     3  2022      32         1 TRUE                    FALSE                  
#> 12     3  2023      33         1 TRUE                    FALSE                  
#> # ℹ abbreviated name: ¹​panelbuild_completed_cell
#> # ℹ 1 more variable: panelbuild_audit_action <chr>