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Indirect calorimetry and oxygen consumption (VO 2 ) are accepted tools in human physiology research. It has been shown that indirect calorimetry systems exhibit differential measurement error, where the error of a device is systematically different depending on the volume of gas flow. Moreover, systems commonly report multiple decimal places of precision, giving the clinician a false sense of device accuracy. The purpose of this manuscript is to demonstrate the use of a novel statistical tool which models the reliability of two specific indirect calorimetry systems, Douglas bag and Parvomedics 2400 TrueOne, as univariate normal distributions and implements the distribution overlapping coefficient to determine the likelihood that two VO 2  measures are the same. A command line implementation of the tool is available for the R programming language as well as a web-based graphical user interface (GUI). This tool is valuable for clinicians performing a single-subject analysis as well as researchers interested in determining if their observed differences exceed the error of the device.

A Statistical Method and Tool to Account for Indirect Calorimetry Differential Measurement Error in a Single-Subject Analysis