jared
d95c9032c5
The Census of Governments is a complete census only in years ending in 2 and
7. Every other year is a sample, and the sample varies enormously. Neither
cog_geographic_rollup() nor cog_peer_compare()/cog_find_peers() had any
concept of "the universe": each summed or labelled whichever govids happened
to have rows and returned that with nothing distinguishing "every government
reported" from "a fifth of them did".
On the bundled fixture, Wisconsin's 608-city universe rolls up 597
governments in FY2012 and 112 in FY2019. The peer side is worse exposure, not
better: a Madison-scale cohort looks stable because Madison is large, while
governments matched to a small target sit in exactly the population band the
sample cycle hits hardest. Chilton's 15-peer cohort reports 15 of 15 in
FY2012 and 3 of 15 in FY2019.
Implements the owner's settled design: coverage = c("all", "census",
"consistent") on all three verbs, defaulting to "all" so nothing currently
calling them changes, PLUS always-on provenance$coverage carrying per-year
n_units_reporting / n_units_expected / is_census_year and
provenance$coverage_mode. cog_explain() prints a "Reporting coverage"
section. The default mode can no longer mislead silently, which is the point
-- using these verbs correctly must not require knowing the survey calendar.
Decisions worth stating:
- n_units_expected is the universe the CALLER named, not the national one.
That is what makes the ratio mean something: "597 of the 608 Wisconsin
cities you asked about". For peers it is the cohort size, counted over
peer rows only -- including the target would inflate every count by one
and make a cohort that has entirely stopped reporting look non-empty.
- The coverage table is built from the REQUESTED years, not the years
present in the result, so a year in which nothing reported still appears
with n_units_reporting = 0. A year that vanishes silently is precisely
the disclosure failure at issue.
- "census" filters years BEFORE the query, and aborts when the range holds
no census year rather than returning an empty result for a query the
caller believes they made.
- "consistent" exempts the peer-comparison target: it is the subject of the
comparison, not a member of the cohort being balanced, and dropping it
would leave nothing to compare. The summary_* quantiles are computed
AFTER the filter so they describe the cohort actually returned.
- is_census_year is documented as a statement about the survey CALENDAR,
never a claim of completeness -- FY1967 is a census year in which only 97
of Wisconsin's 608 cities report (DoD 3). n_units_reporting is the number
that tells the truth.
On cog_find_peers(), where there is no year range, coverage governs the
cohort VINTAGE: "census" snaps to the most recent census year with an
observed population, so a cohort is not built from a sample year in which
most of the candidate universe is absent. "consistent" is a comparison-time
concept and selects like "all" there, carried on the result for
cog_peer_compare().
One fix to the committed test, which was internally inconsistent. It pinned
n_units_reporting == 597 for FY2012 AND asserted that number equals a raw
cross-check that answers 595. Both numbers are right for different questions:
VERNON VILLAGE and WAUKESHA VILLAGE carry type = 3 in `long` (their
as-of-year identity, as townships) while the xwalk lists them as govs_type =
2 (their present identity, as villages) -- schema v6 made the long table's
geography present-harmonized but `type` still reads as-of-year. The rollup
counts against the requested govid set, so 597 answers "how many of the
governments I asked about reported". The cross-check now scopes to that same
universe instead of to long.type/long.fips_state; it still reads raw parquet
rather than going through the verb under test.
Suite: 670 pass / 0 fail / 2 skip (was 658/0/3). rcmdcheck clean.
The two remaining skips are #11 and #12.
108 lines
4.4 KiB
R
108 lines
4.4 KiB
R
# R/coverage.R
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#
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# Reporting-coverage disclosure for the multi-government verbs (uscogdata#13,
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# findings F-020 and F-023).
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#
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# The Census of Governments is a COMPLETE CENSUS only in years ending in 2 and
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# 7. Every other year is a sample, and the sample varies enormously: on the
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# bundled fixture, Wisconsin's 608-city universe reports 597 governments in
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# FY2012 and 112 in FY2019. Summing "whatever reported" across those years is
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# what the verbs have always done -- correctly -- but the return value said
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# nothing about it, so a statewide total resting on 18% of the universe looked
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# exactly like one resting on 98%.
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#
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# Owner's settled design: a `coverage` argument selecting WHICH units to
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# include, plus always-on metadata saying how many there were either way. The
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# principle behind it: using these verbs correctly must not require the caller
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# to know the survey calendar.
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# Years ending in 2 or 7 are full censuses of every government; all others are
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# samples.
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.CENSUS_YEAR_ENDINGS <- c(2L, 7L)
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#' @noRd
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.is_census_year <- function(years) {
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as.integer(years) %% 10L %in% .CENSUS_YEAR_ENDINGS
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}
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#' @noRd
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.validate_coverage <- function(coverage) {
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tryCatch(
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match.arg(coverage, c("all", "census", "consistent")),
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error = function(e) {
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cli::cli_abort(
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"`coverage` must be one of {.val all}, {.val census} or {.val consistent}.",
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class = "uscogdata_invalid_coverage", parent = e
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)
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}
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)
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}
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#' Restrict `years` to census years for `coverage = "census"`.
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#'
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#' Aborts rather than returning an empty result when the requested range holds
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#' no census year: silently handing back zero rows for a query the caller
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#' believes they made is the failure mode this whole issue is about.
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#' @noRd
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.apply_census_years <- function(years, coverage, verb) {
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if (!identical(coverage, "census")) return(as.integer(years))
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keep <- as.integer(years)[.is_census_year(years)]
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if (length(keep) == 0L) {
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cli::cli_abort(c(
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"{.code coverage = \"census\"} leaves no years to query.",
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x = "None of the requested years end in 2 or 7: {.val {sort(unique(as.integer(years)))}}.",
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i = "Census of Governments years ending in 2 or 7 are complete censuses; all others are samples.",
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i = "Use {.code coverage = \"all\"} (the default) to keep every requested year, or request a census year."
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), class = "uscogdata_no_census_years")
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}
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sort(keep)
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}
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#' Keep only units that report in EVERY requested year (a balanced panel).
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#'
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#' `id_col` is the government identifier; `keep_ids` are rows exempt from the
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#' filter (the peer-comparison target, which is the subject of the comparison
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#' rather than a member of the cohort being balanced).
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#' @noRd
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.filter_consistent <- function(result, years, id_col = "canonical_govid",
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keep_ids = character(0)) {
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years <- unique(as.integer(years))
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if (nrow(result) == 0L || length(years) <= 1L) return(result)
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ids <- setdiff(unique(result[[id_col]]), c(NA, keep_ids))
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present <- vapply(ids, function(g) {
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all(years %in% unique(as.integer(result$year[result[[id_col]] == g])))
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}, logical(1))
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consistent <- c(ids[present], keep_ids)
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result[result[[id_col]] %in% consistent | is.na(result[[id_col]]), ,
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drop = FALSE]
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}
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#' Per-year coverage metadata, always attached regardless of mode.
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#'
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#' Built from the REQUESTED years rather than the years present in the result,
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#' so a year in which nothing reported still appears -- with
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#' `n_units_reporting = 0`, which is precisely the disclosure a silently
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#' missing year fails to make.
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#'
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#' `n_units_reporting` describes the result the caller actually received, so
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#' under `coverage = "consistent"` it reports the balanced count. `is_census_year`
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#' is a statement about the SURVEY CALENDAR, never a claim of completeness:
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#' FY1967 is a census year in which only 97 of Wisconsin's 608 cities report.
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#' `n_units_reporting` is the number that tells the truth.
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#' @noRd
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.coverage_table <- function(result, years, n_expected,
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id_col = "canonical_govid", rows = NULL) {
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years <- sort(unique(as.integer(years)))
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src <- if (is.null(rows)) result else rows
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reporting <- vapply(years, function(y) {
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ids <- src[[id_col]][as.integer(src$year) == y]
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length(unique(ids[!is.na(ids)]))
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}, integer(1))
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tibble::tibble(
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year = years,
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n_units_reporting = as.integer(reporting),
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n_units_expected = rep(as.integer(n_expected), length(years)),
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is_census_year = .is_census_year(years)
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)
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}
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