Analysis of the ARSAU aggregate-summary-by-year file (2020-2022).

The aggregate file is a long-format YEAR_2020 / YEAR_2021 / YEAR_2022 panel keyed by (SECTION, CATEGORY, UNITS OF MEASURE). This function rebuilds the implied time series, runs year-on-year change against the REPORT_SCOPE rows (the headline volume series), and surfaces a data-quality audit.

Usage

morie_arsau_analyze_aggregate_summary(
  year_range = "2020-2022",
  language = "en",
  data_dir = NULL
)

Arguments

year_range

"2020-2022".

language

"en" or "fr".

data_dir

Optional explicit ARSAU root.

Value

A list classed c("morie_arsau_result", "morie_rich_result", "list").

References

Ontario Ministry of the Solicitor General, ARSAU 2020-2022 aggregate-summary-by-year technical notes.

Examples

# \donttest{
res <- try(morie_arsau_analyze_aggregate_summary(year_range = "2020-2022"))
if (!inherits(res, "try-error")) print(res)
#> ARSAU aggregate_summary analysis (2020-2022)
#> ============================================
#> Call: morie_arsau_analyze_aggregate_summary(year_range=‘2020-2022’) 
#> 
#>   Year/range        2020-2022
#>   Kind              aggregate_summary
#>   Rows analysed     5
#>   Columns analysed  6
#>   Valid             yes
#>   Sub-analyses      1
#> 
#> Ran 1 sub-analysis(es) over the ARSAU 'aggregate_summary' dataset for '2020-2022': data_quality. Each sub-result is available as `result$<name>` and the underlying data.frame as `result$data`. Year-on-year change is computed against the '1 to 3 Subjects - Individual Reports' REPORT_SCOPE row, which is the headline volume metric in the ministry's annual technical reports. 
# }