prepare_data: Prepares a dataframe for the analysis

In logib: Salary Analysis by the Swiss Federal Office for Gender Equality

Description

Prepares a dataframe for the analysis in three steps:

• Checks whether sex, age, and entry_date have the correct format and whether their specifications are plausible

• Build the dataframe used for the analysis

• Check each row of the dataframe for correctness and plausibility

Usage

prepare_data(
  data,
  reference_month,
  reference_year,
  female_spec = "F",
  male_spec = "M",
  age_spec = NULL,
  entry_date_spec = NULL,
  ignore_plausibility_check = FALSE,
  prompt_data_cleanup = FALSE
)

Arguments

data	a dataframe object as produced by read_data which is to be used in the analysis
reference_month	a number indicating the reference month of the analysis
reference_year	a number indicating the reference year of the analysis
female_spec	a string or number indicating the way females are specified in the dataset.
male_spec	a string or number indicating the way males are specified in the dataset
age_spec	a string indicating the age specification, can be one of NULL, "age", "birthyear", or "date_of_birth". If this parameter is set to NULL, the function automatically tries to infers the specification
entry_date_spec	a string indicating the entry_date specification, can be one of NULL, "years", "entry_year", or "entry_date". If this parameter is set to NULL, the function automatically tries to infers the specification
ignore_plausibility_check	a boolean indicating whether the user wants to ignore implausible data. If TRUE, the implausible data is interpreted as being correct.
prompt_data_cleanup	a boolean indicating whether the user wants to be prompted regarding incorrect data values. If FALSE, the analysis will run without the incorrect data only.

Value

a data.frame which has no incorrect rows left and can be used to estimate the standard analysis model

logib documentation built on Nov. 21, 2021, 9:08 a.m.