Statistical measurement of trees’ similarity

Journal article


Sabbaghan, S. (2020). Statistical measurement of trees’ similarity. Quality and Quantity: international journal of methodology.
AuthorsSabbaghan, S.
Abstract

Diagnostic theories are fundamental to Information Systems practice and are represented in trees. One way of creating diagnostic trees is by employing independent experts to construct such trees and compare them. However, good measures of similarity to compare diagnostic trees have not been identified. This paper presents an analysis of the suitability of various measures of association to determine the similarity of two diagnostic trees using bootstrap simulations. We find that three measures of association, Goodman and Kruskal’s Lambda, Cohen’s Kappa, and Goodman and Kruskal’s Gamma (J Am Stat Assoc 49(268):732–764, 1954) each behave differently depending on what is inconsistent between the two trees thus providing both measures for assessing alignment between two trees developed by independent experts as well as identifying the causes of the differences.

KeywordsDiagnostic theory; Tree; Threshold building
Year2020
JournalQuality and Quantity: international journal of methodology
PublisherSpringer Verlag
ISSN0033-5177
Digital Object Identifier (DOI)doi:10.1007/s11135-019-00957-8
Publication dates
Online03 Jan 2020
Publication process dates
Accepted15 Dec 2019
Deposited09 Jan 2020
Publisher's version
License
CC BY 4.0
File Access Level
Open
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https://openresearch.lsbu.ac.uk/item/88w67

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