daoh 0.2.6

Changes (default units)

• DAOH is now reported in days by default across the package, for a single consistent and interpretable unit. bland_altman_daoh(), plot_daoh_dist(), daoh_reclassify(), daoh_reclassify_centile(), and daoh_icc() now default to use_pc = FALSE (days); pass use_pc = TRUE for percentage of the period.
• daoh_summary() gains a use_pc argument (default FALSE, days).
• Behaviour change: code relying on the previous percentage defaults must now pass use_pc = TRUE. For daoh_icc() and daoh_reclassify() the result is unchanged (the statistic is invariant to the per-period rescaling); for bland_altman_daoh(), plot_daoh_dist(), and daoh_summary() the reported values switch from percentage to days.

daoh 0.2.5

Features

• plot_daoh_ba() gains a show_loa argument. When TRUE, the mean-bias and 95% limits-of-agreement values are printed directly on the plot beside their reference lines (in addition to the caption). Defaults to FALSE, so existing plots are unchanged.

daoh 0.2.4

Changes

• plot_daoh_dist() now labels the y-axis "Count" (the absolute number of observations per bin) rather than the ambiguous "Frequency", and gains a ylab argument to override it.

daoh 0.2.3

Features

• plot_daoh_dist() gains a use_pc argument: set use_pc = FALSE to plot DAOH in days rather than as a percentage of the period (axis label follows).
• bland_altman_daoh() now records units ("%" or "days") in its result, and plot_daoh_ba() labels its axes and caption from that unit, so a Bland-Altman computed with use_pc = FALSE is plotted in days. Results from earlier versions (without units) are still treated as percentages.

daoh 0.2.2

Performance

• bland_altman_daoh(), daoh_reclassify(), daoh_reclassify_centile(), and daoh_icc() now join their inputs with data.table instead of base merge(). On multi-million-row inputs each call is roughly an order of magnitude faster; results are unchanged (row order within the join may differ, which the computed statistics do not depend on).

daoh 0.2.1

Bug fixes

• Timezone handling for POSIXct inputs. Two related defects affected the exact method (and any POSIXct input) on machines whose local timezone is not UTC:
  • as.Date() on POSIXct converts via UTC, so local times earlier than the UTC offset (e.g. mornings in New Zealand) were assigned to the previous calendar day. This shifted index dates and admission/discharge dates.
  • hospital_time() measured exact intervals from the origin at 00:00 UTC, offsetting every value by the local UTC offset (about half a day in NZ) relative to the whole-day numbers used for the index-date period windows, which misaligned all interval clipping at period boundaries.
  Both now use the input’s local calendar date (plus local clock-time fraction for exact). Results from Date inputs are unchanged. Results for POSIXct inputs in non-UTC timezones will change — they were previously wrong.

Tests

• Corrected two test expectations: calc_daoh() returns one row per index date (with daoh = period) when there are no admissions, and the nights-vs-days systematic difference equals the days episode count (same-day stays contribute zero nights, so the nights method does not count them as episodes).
• Added a regression test for local-timezone handling of POSIXct inputs.

daoh 0.2.0

Performance

• calc_daoh() now uses a fully vectorised data.table pipeline instead of an R-level loop over patients. The key changes:
  • foverlaps() matches admissions to index periods in a single C-level pass, correctly handling patients with multiple index dates.
  • Interval merging uses a one-pass cumulative-max sweep (ave()) rather than a sequential R loop per patient, giving O(n log n) overall complexity.
  • Dead time and DAOH are computed by vectorised arithmetic over all patients simultaneously.
  • All column assignments use data.table::set() (no :=), which avoids data.table’s cedta() namespace check and works correctly under both devtools::load_all() and a standard package install.
• data.table (>= 1.14.0) added to Imports.

Bug fixes

• Fixed a latent issue where min(dod) on an empty group (all patients alive) could emit a spurious “no non-missing arguments” warning.

daoh 0.1.0

• Initial CRAN release.
• calc_daoh(): calculates DAOH for one or more patients given a data.frame of admissions and a data.frame of index dates. Supports three hospital-time algorithms (nights, days, exact) and three death-handling methods (midday, midnight, zero). A configurable gap tolerance (default 12 h) merges near-adjacent admissions before summing hospital time.
• hospital_time(): converts admission/discharge date pairs to numeric intervals under the chosen algorithm.
• dead_time(): calculates dead days within a follow-up period.
• merge_intervals(): merges overlapping or near-adjacent intervals with a configurable gap tolerance. Exported for direct use.
• daoh_summary(): summary statistics (mean, SD, percentiles) across a list of calc_daoh() results.
• bland_altman_daoh() / plot_daoh_ba(): Bland–Altman agreement analysis and plot comparing two sets of DAOH values.
• daoh_icc(): intraclass correlation coefficient between two DAOH vectors.
• daoh_reclassify() / daoh_reclassify_centile() / plot_daoh_reclassify(): centile-based reclassification analysis and plot.
• plot_daoh_dist(): distribution plot for a single set of DAOH values.
• load_example(): loads the bundled example dataset.

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