acc_shape_or_scale function

Compare observed versus expected distributions

This implementation contrasts the empirical distribution of a measurement variables against assumed distributions. The approach is adapted from the idea of rootograms (Tukey 1977) which is also applicable for count data (Kleiber and Zeileis 2016).

Indicator

acc_shape_or_scale(
  resp_vars,
  study_data,
  label_col,
  item_level = "item_level",
  dist_col,
  guess,
  par1,
  par2,
  end_digits,
  flip_mode = "noflip",
  meta_data = item_level,
  meta_data_v2
)

Arguments

• resp_vars: variable the name of the continuous measurement variable
• study_data: data.frame the data frame that contains the measurements
• label_col: variable attribute the name of the column in the metadata with labels of variables
• item_level: data.frame the data frame that contains metadata attributes of study data
• dist_col: variable attribute the name of the variable attribute in meta_data that provides the expected distribution of a study variable
• guess: logical estimate parameters
• par1: numeric first parameter of the distribution if applicable
• par2: numeric second parameter of the distribution if applicable
• end_digits: logical internal use. check for end digits preferences
• flip_mode: enum default | flip | noflip | auto. Should the plot be in default orientation, flipped, not flipped or auto-flipped. Not all options are always supported. In general, this con be controlled by setting the roptions(dataquieR.flip_mode = ...). If called from dq_report, you can also pass flip_mode to all function calls or set them specifically using specific_args.
• meta_data: data.frame old name for item_level
• meta_data_v2: character path to workbook like metadata file, see prep_load_workbook_like_file for details. ALL LOADED DATAFRAMES WILL BE PURGED , using prep_purge_data_frame_cache, if you specify meta_data_v2.

Returns

a list with:

• ResultData: data.frame underlying the plot
• SummaryPlot: ggplot2::ggplot2 probability distribution plot
• SummaryTable: data.frame with the columns Variables and FLG_acc_ud_shape

ALGORITHM OF THIS IMPLEMENTATION:

• This implementation is restricted to data of type float or integer.
• Missing codes are removed from resp_vars (if defined in the metadata)
• The user must specify the column of the metadata containing probability distribution (currently only: normal, uniform, gamma)
• Parameters of each distribution can be estimated from the data or are specified by the user
• A histogram-like plot contrasts the empirical vs. the technical distribution

See Also

Online Documentation