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TSEind (version 0.1.0)

Total Survey Error (Independent Samples)

Description

Calculates total survey error (TSE) for one or more surveys, using both scale-dependent and scale-independent metrics. Package works directly from the data set, with no hand calculations required: just upload a properly structured data set (see TESTIND and its documentation), properly input column names (see functions documentation), and run your functions. For more on TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) ; Biemer, Paul et.al. (2017, ISBN:9781119041672); etc.

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Version

Install

install.packages('TSEind')

Monthly Downloads

106

Version

0.1.0

License

GPL (>= 2)

Maintainer

Joshua Miller

Last Published

July 19th, 2019

Functions in TSEind (0.1.0)

Mean absolute error (MAE)

Relative absolute error (RAE)

Mean absolte percentage error (MAPE)

Relative squared error (RSE)

Mean squared error (MSE) with bias-variance decomposition

Symmetric mean absolte percentage error (SMAPE)

Root mean squared error (MAE)

Mean squared logarithmic error (MSLE)

A data set created by merging 1) data from a "gold standard" survey and 2) data from other surveys of the same universe. Data from the "gold standard" survey are assumed to be the survey universe's "actual" response; data from the other surveys have survey error which the functions in 'TSEind' can calculate. Data are organized by survey (columns) and survey question (rows), and their values are the aggregate, "topline" responses to the survey questions which can range from 1 to 99 (the scale used by each survey question).

Root mean squared logarithmic error (RMSLE)

Root relative squared error (RRSE)

Full scale-independent statistics (MAPE, SMAPE, RAE, RSE, and RRSE)

Full scale-dependent statistics (MAE, MSE, RMSE, MSLE, and RMSLE)