create_iycf_plaus

Usage

create_iycf_plaus(
  df_iycf,
  age_months = NULL,
  sex = NULL,
  iycf_8 = NULL,
  iycf_caregiver = NULL,
  yes_value_caregiver = NULL,
  no_value_caregiver = NULL,
  exp_prevalence_mad = NULL,
  exp_sex_ratio = NULL,
  exp_ratio_under6m_6to23m = NULL,
  grouping = NULL,
  uuid = "uuid",
  short_report = FALSE,
  file_path = NULL
)

Arguments

df_iycf: dataframe output of the check_iycf_flag function
age_months: the name of the variable that indicates the age in month of the child
sex: the name of the variable that indicates the sex of the child
iycf_8: the name of the variable that indicates if the meal frequency the child had yesterday. By default "iycf_8"
iycf_caregiver: the name of the variable that indicates if the caregiver of the child is present. By default NULL
yes_value_caregiver: the value of the choice "yes" to all the caregiver column
no_value_caregiver: the value of the choice "no" to all the caregiver column
exp_prevalence_mad: Expected prevalence for Minimum Acceptable Diet (MAD) By default: 0.3:0.7
exp_sex_ratio: Expected sex ratio. By default: 1:1
exp_ratio_under6m_6to23m: Expected age ratio between children under 6 month, and children between 6 and 23 months. By default: 1:4
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 IYCF related plausibility columns

Examples

if (FALSE) { # \dontrun{
  create_iycf_plaus(df_iycf)
} # }