Dillingham, PW, Alsaedi, BSO, Radu, A ORCID: https://orcid.org/0000-0002-5141-1884 and McGraw, CM (2019) Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools. Sensors, 19 (20).

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Abstract

A new software package, ISEtools, is introduced for use within the popular open-source programming language R that allows Bayesian statistical data analysis techniques to be implemented in a straightforward manner. Incorporating all collected data simultaneously, this Bayesian approach naturally accommodates sensor arrays and provides improved limit of detection estimates, including providing appropriate uncertainty estimates. Utilising >1500 lines of code, ISEtools provides a set of three core functions-loadISEdata, describeISE, and analyseISE- for analysing ion-selective electrode data using the Nikolskii-Eisenman equation. The functions call, fit, and extract results from Bayesian models, automatically determining data structures, applying appropriate models, and returning results in an easily interpretable manner and with publication-ready figures. Importantly, while advanced statistical and computationally intensive methods are employed, the functions are designed to be accessible to non-specialists. Here we describe basic features of the package, demonstrated through a worked environmental application.

Item Type: Article
Additional Information: This is the final published version of the article (version of record). It first appeared online via MDPI at https://www.mdpi.com/1424-8220/19/20/4544 - Please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: analytical methods; Bayesian methods; calibration; electrochemistry; limit of detection
Subjects: Q Science > Q Science (General)
Q Science > QD Chemistry
Divisions: Faculty of Natural Sciences > School of Chemical and Physical Sciences
Related URLs:
Depositing User: Symplectic
Date Deposited: 12 Nov 2019 12:43
Last Modified: 18 Dec 2019 11:13
URI: https://eprints.keele.ac.uk/id/eprint/7176

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