Package 'sitrep'

Exported functions from epikit

Description

Exported functions from epikit

Usage

add_weights_cluster(
  x,
  cl,
  eligible,
  interviewed,
  cluster_x = NULL,
  cluster_cl = NULL,
  household_x = NULL,
  household_cl = NULL,
  ignore_cluster = TRUE,
  ignore_household = TRUE,
  surv_weight = "surv_weight",
  surv_weight_ID = "surv_weight_ID"
)

add_weights_strata(
  x,
  p,
  ...,
  population = population,
  surv_weight = "surv_weight",
  surv_weight_ID = "surv_weight_ID"
)

age_categories(
  x,
  breakers = NULL,
  lower = 0,
  upper = NULL,
  by = 10,
  separator = "-",
  ceiling = FALSE,
  above.char = "+"
)

assert_positive_timespan(x, date_start, date_end)

augment_redundant(x, ...)

constrain_dates(i, period_start, period_end, boundary = "both")

dots_to_charlist(parent = 1L)

fac_from_num(x)

find_breaks(n, breaks = 4, snap = 1, ceiling = FALSE)

find_date_cause(
  x,
  ...,
  period_start = NULL,
  period_end = NULL,
  datecol = "start_date",
  datereason = "start_date_reason",
  na_fill = "start"
)

find_end_date(
  x,
  ...,
  period_start = NULL,
  period_end = NULL,
  datecol = "end_date",
  datereason = "end_date_reason"
)

find_start_date(
  x,
  ...,
  period_start = NULL,
  period_end = NULL,
  datecol = "start_date",
  datereason = "start_date_reason"
)

fmt_ci(
  e = numeric(),
  l = numeric(),
  u = numeric(),
  digits = 2,
  percent = TRUE,
  separator = "-"
)

fmt_ci_df(
  x,
  e = 3,
  l = e + 1,
  u = e + 2,
  digits = 2,
  percent = TRUE,
  separator = "-"
)

fmt_count(x, ...)

fmt_pci(
  e = numeric(),
  l = numeric(),
  u = numeric(),
  digits = 2,
  percent = TRUE,
  separator = "-"
)

fmt_pci_df(
  x,
  e = 3,
  l = e + 1,
  u = e + 2,
  digits = 2,
  percent = TRUE,
  separator = "-"
)

gen_polygon(regions)

gen_population(
  total_pop = 1000,
  groups = c("0-4", "5-14", "15-29", "30-44", "45+"),
  strata = c("Male", "Female"),
  proportions = c(0.079, 0.134, 0.139, 0.082, 0.066),
  counts = NULL,
  tibble = TRUE
)

group_age_categories(
  dat,
  years = NULL,
  months = NULL,
  weeks = NULL,
  days = NULL,
  one_column = TRUE,
  drop_empty_overlaps = TRUE
)

merge_ci_df(x, e = 3, l = e + 1, u = e + 2, digits = 2, separator = "-")

merge_pci_df(x, e = 3, l = e + 1, u = e + 2, digits = 2, separator = "-")

rename_redundant(x, ...)

unite_ci(
  x,
  col = NULL,
  ...,
  remove = TRUE,
  digits = 2,
  m100 = TRUE,
  percent = FALSE,
  ci = FALSE,
  separator = "-"
)

zcurve(x, zscore)

See Also

epikit::add_weights_cluster(), epikit::add_weights_strata(), epikit::age_categories(), epikit::assert_positive_timespan(), epikit::augment_redundant(), epikit::constrain_dates(), epikit::dots_to_charlist(), epikit::fac_from_num(), epikit::find_breaks(), epikit::find_date_cause(), epikit::find_end_date(), epikit::find_start_date(), epikit::fmt_ci(), epikit::fmt_ci_df(), epikit::fmt_count(), epikit::fmt_pci(), epikit::fmt_pci_df(), epikit::group_age_categories(), epikit::merge_ci_df(), epikit::merge_pci_df(), epikit::rename_redundant(), epikit::unite_ci(), epikit::zcurve()

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Functions re-exported from apyramid

Description

Functions re-exported from apyramid

Usage

age_pyramid

Format

An object of class function of length 1.

See Also

apyramid functions:

• apyramid::age_pyramid(): Plot a population pyramid (age-sex) from a dataframe

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Functions re-exported from epitabulate

Description

Functions re-exported from epitabulate

Usage

attack_rate(
  cases,
  population,
  conf_level = 0.95,
  multiplier = 100,
  mergeCI = FALSE,
  digits = 2
)

See Also

epitabulate functions:

• epitabulate::attack_rate(),

• epitabulate::case_fatality_rate()

• epitabulate::case_fatality_rate_df(),

• epitabulate::mortality_rate()

• epitabulate::add_ar(): a gtsummary wrapper for epitabulate::attack_rate()

• epitabulate::add_cfr(): a gtsummary wrapper for epitabulate::case_fatality_rate()

• epitabulate::add_crosstabs(): a gtsummary wrapper to add counts to a gtsummary::tbl_uvregression()

• epitabulate::add_mr(): a gtsummary wrapper for epitabulate::mortality_rate()

• epitabulate::gt_mh_odds(): a gtsummary wrapper for stratified univariate regression and mantel-haenszel estimates

• epitabulate::gt_remove_stat(): a gtsummary wrapper to remove variables from a gtsummary table

• epitabulate::tab_linelist(): tabulate linelist data

• epitabulate::tab_survey(): tabulate survey data

• epitabulate::tab_univariate(): caluclate odds, risk, and incidence risk ratios for multiple variables from linelist data.

• epitabulate::data_frame_from_2x2(): convert a 2x2(x2) table to a data frame clearly labelling the (un)exposed (non)case combinations and their totals.

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Display the available sitrep templates

Description

Display the available sitrep templates

Usage

available_sitrep_templates(categorise = FALSE, ...)

Arguments

categorise	if TRUE, the results are split into a list of outbreak and survey categories. Defaults to FALSE.
...	options to pass on to dir

Value

a vector of available templates in the sitrep package

Examples

available_sitrep_templates(categorise = TRUE)
available_sitrep_templates(categorise = TRUE, full.names = TRUE)

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Functions re-expored from epidict

Description

Functions re-expored from epidict

Usage

msf_dict(
  disease,
  name = "MSF-outbreak-dict.xlsx",
  tibble = TRUE,
  compact = TRUE,
  long = TRUE
)

msf_dict_survey(
  disease,
  name = "MSF-survey-dict.xlsx",
  tibble = TRUE,
  compact = TRUE,
  long = TRUE,
  template = TRUE
)

msf_dict_rename_helper(
  disease,
  name,
  varnames = "data_element_shortname",
  varnames_type,
  rmd,
  template = TRUE,
  copy_to_clipboard = TRUE
)

gen_data(
  dictionary,
  varnames = "data_element_shortname",
  numcases = 300,
  org = "MSF"
)

See Also

Dictionaries: epidict::msf_dict(), epidict::msf_dict_survey()
Renaming: epidict::msf_dict_rename_helper()
Generator: epidict::gen_data()

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