create_mortality_plaus

Usage

create_mortality_plaus(
  df_mortality,
  df_main = NULL,
  uuid_main = NULL,
  date_dc = NULL,
  date_recall_event = NULL,
  num_join = NULL,
  num_left = NULL,
  enumerator = NULL,
  exp_sex_ratio = NULL,
  exp_ratio_0_4 = NULL,
  exp_ratio_2_5 = NULL,
  exp_ratio_5_10 = NULL,
  exp_hh_size = NULL,
  grouping = NULL,
  uuid = "uuid",
  short_report = FALSE,
  file_path = NULL
)

Arguments

df_mortality: output dataframe long mortality from create_mortality_long_df
df_main: main dataset that include the num_ columns
uuid_main: the name of the variable that indicates the unique uuid By default: NULL
date_dc: the name of the variable that indicates the date of data collection By default: NULL
date_recall_event: the name of the variable that indicates the recall date By default: NULL
num_join: variable name indicating the num_join in main dataset
num_left: variable name indicating the num_left in main dataset
enumerator: the enumerator column in main dataset, by default: enumerator
exp_sex_ratio: expected sex ratio in the population of male:female By default: 1:1
exp_ratio_0_4: expected age ratio of <5years to >5years in the population By default: 0.2:0.8
exp_ratio_2_5: expected age ratio of children 0-<2 years to children 2-<5years in the population By default: 0.4118:0.5882
exp_ratio_5_10: expected age ratio of children 0-<5 years to children 5-<10years in the population By default: 0.5238:0.4762
exp_hh_size: expected hh size in the population. By default: 5
grouping: the name of the variable that indicates the grouping variable - usually "enumerator"
uuid: uuid variable
short_report: Inputs a boolean value TRUE or FALSE to return just key variables. If FALSE, returns a dataframe of all the variables calculated.
file_path: Inputs an optional character value specifying the file location to save a copy of the results.

Value

a dataframe with all mortality related plausibility columns

Examples

if (FALSE) { # \dontrun{
  create_mortality_plaus(df_mortality)
} # }