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R.C. McDowall is the principle of McDowall Consulting and director of R.D. McDowall Limited, and "Questions of Quality" column editor for LCGC Europe, Spectroscopy's sister magazine.

Articles

Spreadsheets are often used to perform GMP-related calculations, but can lead to serious problems and unnecessary risk. We explain why the use of spreadsheets is heavily discouraged in a regulated laboratory environment.

Spreadsheets: A Sound Foundation for a Lack of Data Integrity?

Jerome Workman Jr. serves on the Editorial Advisory Board of Spectroscopy and is currently with Unity Scientific LLC. He is also an adjunct professor at Liberty University and U.S. National University. He can be reached at jworkman04@gsb.columbia.edu.

Howard Mark serves on the Editorial Advisory Board of 

 and runs a consulting service, Mark Electronics that provides assistance, training, and consultation in near-IR spectroscopy as well as custom hardware and software design and development.

We provide a scorecard of chemometric techniques used in spectroscopy. The tables and lists of reference sources given here provide an indispensable resource for anyone seeking guidance on understanding chemometric methods or choosing the most suitable approach for a given analysis problem.

A Survey of Chemometric Methods Used in Spectroscopy

Chemometrics in Spectroscopy is a collection of column articles that the authors published in Spectroscopy over a period spanning more than two decades. Each article is generally arranged as a chapter in the book, and chapters dealing with the same or similar topics are arranged closely as a section block rather than following the original sequence in the magazine. Although each article or series of articles only discusses one specific topic, collectively, the articles form a comprehensive reference that is a valuable source for readers wanting to learn chemometrics, especially with its applications in spectroscopy. 


Book Review: Chemometrics in Spectroscopy, 2nd Edition, by Howard Mark and Jerry Workman, Jr.

A newly discovered effect can introduce large errors in many multivariate
spectroscopic calibration results. The CLS algorithm can be used to explain this effect. Having found this new effect that can introduce large errors in calibration results, an investigation of the effects of this phenomenon to calibrations using principal component regression (PCR) and partial least squares (PLS) is examined.

More About CLS, Part 1: Expanding the Concept

Calibration transfer involves multiple strategies and mathematical techniques for applying a single calibration database to two or more instruments. Here, we explain the methods to modify the spectra or regression vectors to correct differences between instruments.

Calibration Transfer Chemometrics, Part I: Review of the Subject

The archnemesis of calibration modeling and the routine use of multivariate models for quantitative analysis in spectroscopy is the confounded bias or slope adjustments that must be continually implemented to maintain calibration prediction accuracy over time. A perfectly developed calibration model that predicted well on day one suddenly has to be bias adjusted on a regular basis to pass a simple bias test when predicted values are compared to reference values at a later date. Why does this problem continue to plague researchers and users of chemometrics and spectroscopy?

Optimizing the Regression Model: The Challenge of Intercept–Bias and Slope “Correction”

When using any regression technique, either linear or nonlinear, there is a rational process that allows the researcher to select the best model.

Choosing the Best Regression Model

The statistical methods used for evaluating the agreement between two or more instruments (or methods) for reported analytical results are discussed, with an emphasis on acceptable analytical accuracy and confidence levels using two standard approaches, standard uncertainty or relative standard uncertainty, and Bland-Altman "limits of agreement."

Calibration Transfer, Part IV: Measuring the Agreement Between Instruments Following Calibration Transfer

This article describes the application of chemometric methods and statistics for reporting clinical quantitative measurement methods. The equations and terminology are consistent with the Clinical and Laboratory Standards Institute (CLSI) guidelines. These chemometric and statistical methods describe the accuracy and precision of a test method compared to a reference method for a single analyte determination. Part I will introduce these concepts and Part II will discuss the statistical underpinnings in greater detail.

Statistics and Chemometrics for Clinical Data Reporting, Part I

Columnists Howard Mark and Jerome Workman, Jr. take a final look at the topic of principal components, which has been the subject of six previous installments.

Data Analysis, Statistics, and Chemometrics