ArticleSensors (Basel, Switzerland)2022
Evaluation of Calibration Equations by Using Regression Analysis: An Example of Chemical Analysis.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Evaluation of isotope-dilution mass spectrometry, internal standard, and external standard methods for PFAS quantification in tap water and soil.Analytical and bioanalytical chemistry · 2026Article
- Identification and Regulation of Melatonin Biosynthetic Genes in Sweet Pepper During Ripening and Melatonin Treatment.Antioxidants (Basel, Switzerland) · 2026Article
- Experimental Laboratory Study on the Acoustic Response Characteristics of Fluid Flow in Horizontal Wells Based on Distributed Fiber Optic Sensing.Sensors (Basel, Switzerland) · 2026Article
- First In Vitro Human Islet Assessment of Oleanolic Acid (OA) and Its Serine Conjugate: Enhanced Solubility with Comparable Effects.Molecules (Basel, Switzerland) · 2025Article
- SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0.Analytical chemistry · 2025Article
- Comparison of Classical and Inverse Calibration Equations in Chemical Analysis.Sensors (Basel, Switzerland) · 2024Article
- Investigating the Quantification Capabilities of a Nanopore-Based Sequencing Platform for Food Safety Application via External Standards of Lambda DNA and Lambda Spiked Beef.Foods (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A calibration curve is used to express the relationship between the response of the measuring technique and the standard concentration of the target analyst. The calibration equation verifies the response of a chemical instrument to the known properties of materials and is established using regression analysis. An adequate calibration equation ensures the performance of these instruments. Most studies use linear and polynomial equations. This study uses data sets from previous studies. Four types of calibration equations are proposed: linear, higher-order polynomial, exponential rise to maximum and power equations. A constant variance test was performed to assess the suitability of calibration equations for this dataset. Suspected outliers in the data sets are verified. The standard error of the estimate errors,
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