The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
histgroup_iarc()
to create variable for groups of malignant neoplasms considered to be histologically ‘different’ for the purpose of defining multiple tumors, ICD-O-3 (see #100)quiet
argument to suppress rlang::warn()
and rlang::inform()
messages. You can use this when you have checked your results for correctness and want to reduce message output, but keep the progress bars.asir()
: add World Standard Population 2000-2025 for function with option std_pop=="WHO2000"
as described here: https://seer.cancer.gov/stdpopulations/world.who.htmlsir_byfutime()
gains new argument expect_missing_refstrata_df
. You can define another dataframe that contains strata expected to be missing from refrates_df (because they are not explicitly coded with incidence = 0). This can be helpful, if refrates_df has a lot of strata and 0 incidence strata have been removed to save storage space. Internally, the rows of expect_missing_refstrata_df will be appended to refrates_df. This reduces the number of lines reported in attribute problems_missing_ref_strata
. Default setting is expect_missing_refstrata_df = NULL
.data("us_second_cancer")
gains new variable t_hist
on histology, i.e. ICD-O-3-Code on tumor morphology (4 digits)calc_refrates()
more robust for missing race_var
(Closes #89)calc_refrates()
using calc_totals == TRUE
(Closes #90)calc_refrates()
using numeric versions of fill_sites
(Closes #92)asir()
that throws error for variable not needed (Closes #95)cli
verb.()
syntax from tidytable (Closes #94)calc_refrates()
to calculate age-, sex-, region-, year-specific reference rates from a long format dataframe with cancer cases that are counted for incident cases and then matched with a reference population. The resulting reference rates dataframe can directly be used with sir_byfutime()
function.dattype = NULL
and thus are more flexible to take other source data types (Closes #73)asir
, calc_futime*
, calc_refrates
, ir_crosstab_byfutime
, pat_status*
, renumber_time_id*
, and sir_byfutime
now by default are set to dattype = NULL
. If you relied on automatic variable naming feature, you need to add dattype = "seer"
or dattype = "zfkd"
to your function call.problems_missing_count_strata
and problems_missing_fu_strata
(Closes #80)sir_byfutime()
:
results_df
tidytable
package have been replaced (Closes #71 and #74)sir_ratio()
and related sir_ratio_lci()
and sir_ratio_uci()
to calculate ratio of two SIRs/SMRs to get relative risk and confidence limits for this ratio.reshape_long_tt()
⇒ the _tt variants usually have smaller memory use than tidyverse and data.table variants. Execution time is usually much faster than tidyverse and comparable to or a little slower than the data.table variant.summarize_sir_results()
:
sir_byfutime()
summarize_sir_results()
:
summarize_site == TRUE
. Previously the results incorrectly counted each site multiple times. (Closes #62)pat_status()
:
dattype = "zfkd"
data("standard_population")
data("population_us")
(Closes #58)sir_byfutime()
: change output of integer columns to numeric to fix bug in summarize_sir_results()
(Closes #59)vignette("introduction")
reshape_wide_tt()
, renumber_time_id_tt()
, pat_status_tt()
, vital_status_tt()
, calc_futime_tt()
⇒ the _tt variants usually have smaller memory use than tidyverse and data.table variants. Execution time is usually much faster than tidyverse and comparable to or a little slower than the data.table variant.sir_byfutime()
:race_var
to optionally stratify SIR calculations by race.summarize_sir_results()
:sir_byfutime()
functionsite_var_name
sir_byfutime()
:
add_total_row
and add_total_fu
are replaced by calc_total_row
and calc_total_fu
. These are logical parameters now. The positioning of total rows and columns is completely handled by the summarize_sir_results()
function now. There total rows can be set to top and bottom and total columns to left and right.expcount_src
including related parameters stdpop_df
, refpop_df
, std_pop
, truncate_std_pop
and pyar_var
have been removed. Function sir_byfutime()
will only work calculating expected counts based on reference rates, not within the cohort of the dataset. To calculate expected based on the cohort, a new function create_refrates
will be added in the future. (#41)collapse_ci
has been removed and added to summarize_sir_results()
instead.icdcat_var
to site_var
agegroup_var
to age_var
expcount_src
, futime_src
, stdpop_df
, refpop_df
, std_pop
, truncate_std_pop
, pyar_var
, icdcat_var
, collapse_ci
have been removed to simply the function ⇒ make sure you remove these arguments from your sir_byfutime()
function calls.sir()
:
sir_byfutime()
. To migrate your former sir()
functions, you can simply use sir_byfutime(, futime_breaks = "none")
that will yield the same results.summarize_sir_results()
:
summarize_icdcat
to summarize_site
reshape_long_tidyr()
:
var_selection
is deprecated. Please select variables before running the reshape_long_*
functions.asir()
:
agegroup_var
to age_var
icdcat_var
to site_var
pat_status()
, pat_status_tt()
, vital_status()
, and vital_status_tt()
:
ir_crosstab_byfutime()
:
futime_breaks
now uses breaks in years instead of months as previously.futime_var
is now follow-up time in yearsicdcat_var
to site_var
. This need manual update of function calls of sir_byfutime()
and asir()
, if option is specified.t_icdcat
to t_site
. So the reference data frames used will need to have a t_site
column.renumber_time_id_dt()
, pat_status_dt()
, reshape_long_dt()
, reshape_wide_dt()
, vital_status_dt()
) have been removed for simplicity, please use tidytable variants, i.e. reshape_wide_tt()
, renumber_time_id_tt()
, pat_status_tt()
, vital_status_tt()
, calc_futime_tt()
, instead. They will give the same data.table output and same performance.reshape_wide()
with option chunks
is used. Closes #1.reshape_wide_tidyr()
and reshape_wide_tt()
is now preserved. Closes #31.renumer_time_id()
and make sure that new_time_id_var
is returned as integer.pat_status_*(., check = TRUE)
optionsir_byfutime()
so that PYARs do not get lost before running summary functionsir_byfutime()
now also gives correct results if range of futime_breaks
is not 0-Inf but smallerrenumber_time_id()
function; use sorting by date of diagnosis instead of old time_id_varreshape_wide_tidyr()
functionreshape_wide_dt()
function which is much faster now and uses data.table::dcast
instead of stats::reshape
nowpat_status()
and pat_status_dt()
functionssummarize_sir_results()
is now functionalvignette("introduction")
pat_status()
and pat_status_dt()
functionsrenumber_time_id()
that broke functionspat_status()
and calc_futime()
tidyselect::all_of
in summarize_sir_results()
vignette("patstatus_futime")
tidyselect::all_of
for vector-based variable selectionvital_status_dt
and pat_status_dt
data.table
reshape_long
function workadd_total_row
work, even if option ybreak_vars = "none"
NEWS.md
file to track changes to the package.futime_breaks = "none"
to sir_byfutime
functionThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.