Changes in version 0.7.2 (2026-01-18)                  

  - Bug fixes:
      - survdiff_ci() now uses the conf.level argument correctly in
        confidence interval estimation using the MOVER approach (#8).
  - Internal:
      - Anticipate changes in {dplyr} 1.2.0 in label handling in unit
        tests (thanks to @DavisVaughan, #10).

                 Changes in version 0.7.1 (2025-06-06)                  

  - Housekeeping for CRAN release

                        Changes in version 0.7.0                        

  - Breaking changes:
      - Require base R pipe |> and thus R >= 4.1.
      - Make the id variable identifying clustered observations within
        the same individual a global rifttable() option for the entire
        data set, not only for specific estimators.
  - New functionality:
      - Expand input checks to missing values in time/event variables,
        to missing effect modifiers for joint models and their levels,
        to nonexistent custom estimators, and to empty input data sets.
      - Add type = "sum" estimator.
  - Internal and bug fixes:
      - Cover entire package by unit tests.
      - Return exposure consistently as a character.
      - Let the design accept weight in addition to weights.
      - Require {risks} >= 0.4.3.
      - Use modern tidyselect, anonymous functions, and code style.

                        Changes in version 0.6.3                        

  - New functionality:
      - Provide easier interface to code competing events by directly
        providing event = "event_variable@Event_Type_One" in the design.
        If multiple event types are present, estimate cumulative
        incidence and differences/ratios of cumulative incidence in a
        competing-event setting.
      - Allow for clustered observations in survival data, e.g.,
        multiple rows per person.
      - Estimate ratios of survival and cumulative incidence, i.e.,
        x-year risk ratios. Use MOVER estimation for confidence
        intervals of both ratios and differences in survival and
        cumulative incidence by default.
      - Support weights, e.g., inverse-probability weights, directly via
        a weights argument in the design. Weighted estimates are
        currently available for many survival estimators: type =
        "cuminc", "surv", their differences and ratios (e.g.,
        "cumincdiff"), and "hr". This is a breaking change for Cox
        models (type = "hr"), where providing weights in the arguments
        list now generates an error.
  - Bug fixes:
      - Allow for @ in factor levels for a table1_design().
      - rt_gt(): Output knitr-formatted tables for GitHub-flavored
        markdown also in Quarto .qmd, similar to .Rmd.
      - Better handling of edge cases, e.g., ratios of 0, when rounding
        estimates.
  - Expanded documentation
      - Restructure site.
      - Separate documentation of estimators by outcome type.
      - New FAQs on confidence levels, reference levels, custom
        functions, and joint models.

                        Changes in version 0.6.2                        

  - New functionality:
      - Add overall argument exposure_levels to let user control
        handling of missing exposure levels (NA) or factors with empty
        levels as the exposure.
      - type = "geomean" for geometric means.
  - Documentation: Expand FAQs.
  - Internal and bug fixes:
      - Consider exposure or trend of "" as missing, and stratum = "" as
        no subsetting by the effect_modifier, instead of subsetting to
        effect modifier being an empty string. Input check that a
        stratum must be provided for joint models and strata are not
        empty.
      - Consider missing type as "blank".
      - Do not add empty rows/columns if type2 has empty results for
        some cells or if only a trend variable and no exposure is given.
      - Rounding works even if result vector contains strings (e.g., no
        estimate).
      - More safeguards for all-NA outcome variables. More input checks.
      - Do not warn about non-0/1 outcomes in log-linear models for
        ratios of continuous variables.
      - Add initial set of unit tests.

                        Changes in version 0.6.1                        

  - New functionality:
      - Cox models (type = "hr") allow for weights, clustering, and
        robust standard errors.
      - Argument ratio_digits_decrease: By default, decrease number of
        decimal digits shown for ratios by 1 digit for ratios > 3 and
        by 2 digits for ratios
        10. Leads to rounded ratios and confidence intervals of 1.23,
            3.4, and 11.
    
      - rt_gt() now indents the first column and applies markdown
        formatting to it by default.
  - New FAQ vignette.
  - Bug fixes:
      - Binary outcomes returned NA instead of 0 in unstratified tables
        with all-null outcome.
      - type = "maxfu" ignored digits and diff_digits.
      - Allow for different exposure (strata labels) and arguments in
        one table.
      - Show unstratified estimate if exposure is "", not just for NA.
  - Internal:
      - rt_gt(): suppress random id of gt tables to keep git diff slim.
      - Keep variables .event, .outcome, etc. available under their
        original names.
      - Require {risks} >= 0.4.2.
      - Examples load the breastcancer dataset from the risks package.

                        Changes in version 0.6.0                        

  - Breaking changes:
      - to is set to ", " by default, instead of "-" for ratio variables
        and " to " for difference variables
      - Custom functions are now directly called via the type variable,
        following a restructuring of all estimation functions with
        greater flexibility.
      - design$type no longer accepts additional arguments, such as time
        points. Supply list instead via design$arguments.
      - Suppression of strata with sparse or re-identifiable data with
        design$nmin now differentiates between counts of total
        observations or outcomes, depending on estimator.
  - New function table1_design(): Generate design of a descriptive
    "Table 1."
  - New outcome option "variable@level" for categorical variables that
    displays level as a binary outcome. Used by table1_design().
  - Support unstratified tables displaying the trend/linear slope (trend
    variable in the design) without an exposure.
  - More customization:
      - rifttable(reference = ...): Label for the reference category.
      - design$ci: Width of confidence intervals.
      - design$na_rm: Omitting observations with missing outcome data.
      - design$arguments: Flexibly passing along any argument to
        estimation functions.
  - New vignette describing all estimators.
  - Internal:
      - Drop dependency on R >= 4.1 and native pipe.
      - Require {risks} >= 0.4.0.
      - Remove dependency on {labelled} package.
      - The {gt} and {quantreg} packages are now optional as soft
        dependencies.
      - Compatible with {dplyr} 1.1.0, {tidyselect} 1.2.0

                        Changes in version 0.5.0                        

  - khsmisc::table2() "graduated" into its own package. See {khsmisc}
    Changelog for earlier versions.
  - Add breastcancer() dataset
  - Use R >= 4.1 native pipe, |>
  - Remove RMTL estimators