mean_proportion_table: Analyze and aggregate weighted categorical data into clean...

In zackarno/butteR: Smoothes out analysis work flow especially when using mobilie data collection systems (ODK/Kobo)

Description

Analyze and aggregate weighted categorical data into clean tables

Usage

mean_proportion_table(
  design,
  list_of_variables,
  aggregation_level = NULL,
  round_to = 2,
  return_confidence = FALSE,
  na_replace = FALSE,
  questionnaire = NULL
)

Arguments

design	Design object from survey or srvyr package.
list_of_variables	Vector containing column names to analyze.
aggregation_level	Column name to aggregate or dissagregate to OR vector of column names to dissagregate to.
round_to	Decimal place to round to.
return_confidence	Logical value specifying whether to return confidence interval (default = FALSE).
na_replace	Logical value (default = FALSE) of whether to replace NA with 0 (numerical) or "filtered" (categorical)
questionnaire	Questionnaire generated from koboquest. If NULL (default) function will attempt to detect select multiple questions automatically. If you have made new indicators which use periods in there names you must remove them from the list_of_variables if you do not supply the koboquest generated questionnaire.

Value

Analyzed table of variables.

zackarno/butteR documentation built on May 8, 2021, 4:50 p.m.