transform_mos {transformmos}

Implementation of MOS-transformation to be used with Rank based statistical techniques.

Description

The rank correlation coefficients and the ranked-based statistical tests (as a subset of non-parametric techniques) might be misleading when they are applied to subjectively collected opinion scores. Those techniques assume that the data is measured at least at an ordinal level and define a sequence of scores to represent a tied rank when they have precisely an equal numeric value. Before applying any rank based static technique use this package to transfer MOS values to a new rank so the result of statistic techniques will be robus to noises.

Usage

transform_mos(mos, ci)

Arguments

mos

array of MOS values

ci

array of 95% Confifence Intervals.

Details

See the paper for details:

Naderi B, Möller S. Transformation of Mean Opinion Scores to AvoidMisleading of Ranked based Statistical Techniques 2020 Twelfth International Workshop on Quality of Multimedia Experience (QoMEX). IEEE, 2020.

There, we show that the definition of tied rank, as mentioned above, is not suitable for Mean Opinion Scores (MOS) and might be misleading conclusions of rank-based statistical techniques. Furthermore, we introduce a method to overcome this issue by transforming the MOS values considering their 95% Confidence Intervals. The rank correlation coefficients and ranked-based statistical tests can then be safely applied to the transformed values. This is the R implementation of the transformation method.

Value

New rank values. Use the outcome with rank based statitical techniques e.g. Spearman's Rank correlation.

Author(s)

Dr. Babak Naderi [e-mail]

References

Naderi B, Möller S. Transformation of Mean Opinion Scores to AvoidMisleading of Ranked based Statistical Techniques. Twelfth International Workshop on Quality of Multimedia Experience (QoMEX). IEEE, 2020.

website: https://github.com/babaknaderi/MOS-transformation

Examples

  mos <- c(1.1, 4, 5, 2, 3, 1.2, 4)
  ci <- c(0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1)
  transform_mos(mos,ci)