Validation and Peer Review 

of U.S. Environmental Protection Agency 

Chemical Methods of Analysis

Prepared for: 

The EPA Forum on Environmental Measurements (FEM) 

Prepared by: 

The FEM Method Validation Team 

FEM Document Number 2005-01 

October 14, 2005 

Principal Authors: 

Elizabeth A. Mishalanie, Ph.D. Barry Lesnik Roy Araki Robin Segall 

National Enforcement Office of Solid Waste US EPA Region 10 Office of Air Quality Planning and 

Investigations Center Washington, DC Seattle, Washington Standards 

Denver, Colorado Research Triangle Park, North Carolina 

Contributors: 

David J. Munch Mike Wasko Elizabeth Flynt 

Office of Water US EPA Region 4 Office of Pesticide Programs 

Office of Groundwater Athens, Georgia Stennis Space Center, Mississippi 

and Drinking Water 

Cincinnati, Ohio 

Steven C. Wendelken, Ph.D. Jenny Scifres John R. Mario 

Office of Groundwater US EPA Region 4 Suffolk County Crime Laboratory 

and Drinking Water Athens, Georgia Hauppauge, New York 

Cincinnati, Ohio 

Margo Hunt Diane Gregg Teri Schaeffer 

Office of Environmental Information US EPA Region 6 Versar, Inc. 

Washington, DC Houston, Texas Springfield, Virginia 

Meredith Clarage M. Susan Lumpkin 

US EPA Region 6 National Exposure Research Laboratory 

Houston, Texas Research Triangle Park, North Carolina 
Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

Disclaimer 

This document contains direction developed solely to provide internal guidance to U.S. 

Environmental Protection Agency (EPA) personnel. EPA retains the discretion to adopt approaches 

that differ from this guidance on a case-by-case basis. The guidance set forth in this document does 

not create any rights, substantive or procedural, enforceable at law by a party to litigation with EPA 

or the United States. The use of mandatory language such as "must" and "require" in this guidance 

document reflects sound scientific practice and should not be construed to create any legal rights or 

requirements. The use of non-mandatory language such as "may," "can," or "should" in this 

guidance does not connote a requirement but does indicate EPA’s strongly preferred approach for 

validating and peer reviewing EPA methods prior to publication for general use. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

Foreword 

The U.S. EPA Science Policy Council established the Forum on Environmental 

Measurements (FEM) in April 2003. The FEM is a standing committee of senior EPA managers 

who provide EPA and the public with a focal point for addressing measurement and methods issues 

with multiprogram impact. Action teams are commissioned by the FEM to address specific issues. 

The Method Validation Team was formed in October 2003, and tasked with developing Agencywide, internal guidance for validating and peer reviewing EPA methods prior to publication for 

general use. 

This document contains guidance for chemical methods of analysis. It is the first in a series 

of Agency-wide, method validation guidance documents. Subsequent guidance will be developed 

for other types of measurement methods (e.g., microbiology, biology, toxicology, radiochemistry, 

and field procedures). 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

Executive Summary 

EPA program offices publish a wide variety of measurement methods for use by EPA 

personnel, other government agencies, and the private sector. These methods may originate from 

many sources such as EPA laboratories, EPA contractors, scientific organizations, other government 

laboratories, and from the private sector. Since these methods may be published as regulations, 

incorporated by reference in regulations, or published as guidance, they must be thoroughly tested 

and peer reviewed prior to publication as EPA methods. 

This document provides Agency-wide guidance for EPA personnel who will evaluate the 

performance and suitability of new chemical methods of analysis before EPA publication. The 

method validation principles contained herein are based on current, international approaches and 

guidelines for intralaboratory (single laboratory) and interlaboratory (multiple laboratory) method 

validation studies. Peer review is required for EPA chemical methods of analysis. The EPA Science 

Policy Council Peer Review Handbook provides Agency-wide requirements and options for that 

process. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

Table of Contents 

Disclaimer ....................................................................................................................................... i 

Foreword........................................................................................................................................ ii 

Executive Summary..................................................................................................................... iii 

1 Introduction........................................................................................................................1 

1.1 Purpose........................................................................................................................1 

1.2 Intended Audience ......................................................................................................1 

1.3 Scope of Guidance ......................................................................................................1 

1.4 Terminology................................................................................................................2 

2 Planning and Initiating Method Validation Studies.......................................................3 

3 Method Description ...........................................................................................................4 

3.1 Procedures Composing a Method ...............................................................................4 

3.2 Method Purpose, Scope, and Applicability ................................................................4 

4 Method Performance Characteristics..............................................................................5 

4.1 Selectivity ...................................................................................................................6

 4.2 Instrument Calibration ................................................................................................6 

4.3 Bias/Trueness..............................................................................................................7 

4.4 Precision......................................................................................................................8 

4.5 Quantitation Limits and Range ...................................................................................9 

4.6 Detection Limit(s).......................................................................................................9

5 Ruggedness Testing..........................................................................................................10 

6 Interlaboratory Studies ...................................................................................................11 

7 Method Validation Reports.............................................................................................12 

8 Peer Review ......................................................................................................................13 

9 Terms and Definitions .....................................................................................................14

10 References.........................................................................................................................18 

TABLE 

1 Method Validation Report Topic Areas.............................................................................12 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

1 Introduction 

Method validation is the process of demonstrating that an analytical method is suitable for its 

intended use, and involves conducting a variety of studies to evaluate method performance under 

defined conditions (1). Method validation studies may involve a single laboratory (intralaboratory) 

or multiple laboratories (interlaboratory). The goal is to demonstrate that analytical results produced 

by the application of a particular method are fit for an intended purpose (1). Properly designed and 

successful method validation studies create confidence in the reliability of a test method. Method 

validation is one of several important quality system components that are designed to ensure the 

production of scientifically valid and useful analytical data (2). 

EPA’s chemical methods of analysis are designed for a wide variety of measurement 

objectives, such as monitoring compliance with environmental regulations, enforcement of 

environmental regulations, and for information-gathering scientific studies. Because measurement 

objectives and data quality requirements vary, the technical details and acceptance criteria for 

conducting method validation studies are contained in existing, program-specific EPA documents 

rather than in an Agency-wide guidance. Therefore, this guidance document describes fundamental 

method validation principles and general areas to be addressed when validating chemical methods of 

analysis. This information is based on current, international approaches and guidelines for single 

and multiple laboratory method validation studies. 

Before publication, all chemical methods of analysis also must be peer reviewed. The reader 

is referred to the most current version of the EPA Science Policy Council Peer Review Handbook 

(3), an excellent source of information for both internal and external peer review processes. 

1.1 Purpose 

The purpose of this guidance is to (a) describe scientific principles that should be addressed 

during method validation studies, and (b) harmonize terms and definitions related to analytical 

chemistry method validation studies and method performance characteristics. 

1.2 Intended Audience 

This guidance is intended for internal use by EPA personnel who are responsible for 

chemical methods of analysis, as defined in section 1.3 of this document, that either are to be 

published as serially numbered EPA methods, or published as, or incorporated by reference in, 

regulations. 

1.3 Scope of Guidance 

This guidance contains recommendations for validating new, rational, quantitative, chemical 

methods of analysis, intended for use in analytical laboratories. These terms are defined as follows: 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

• “New” means that the method is not currently published as an EPA method, or it is an update 

of a published EPA method that includes procedural changes that will affect method 

performance. 

• “Rational,” as opposed to empirical, means that the analytical results are not intended to be 

method dependent. A rational method of analysis is a method that determines one or more 

identifiable chemicals or analytes for which there may be several equivalent methods of 

analysis available. Empirical methods determine a value that can be arrived at only in terms 

of the method per se and serves, by definition, as the only method for establishing the 

measurand1 

. This guidance does not explicitly address empirical methods, which are used to 

estimate method-defined parameters. Examples of rational methods are Method 8260 

(Volatile Organic Compounds by Gas Chromatography/Mass Spectrometry, SW-846), 

Method 200.8 (Determination of Trace Elements in Waters and Wastes by Inductively 

Coupled Plasma-Mass Spectrometry), and Method 26 (Determination of Hydrogen Chloride 

Emissions from Stationary Sources, 40 CFR Part 60, Appendix A). Examples of empirical 

methods are Method 1311 (Toxicity Characteristic Leaching Procedure, SW-846), Method 

1664 (Oil and Grease), and Method 5 (Determination of Particulate Matter Emissions from 

Stationary Sources, 40 CFR Part 60, Appendix A). 

• “Quantitative” means that the method is intended to produce numerical results (analyte 

concentration or other quantity) and an estimate of the associated measurement uncertainty 

(4). 

• “Chemical methods of analysis, intended for use in analytical laboratories” means that the 

method primarily is intended for use in a laboratory to measure chemical properties. 

Although some methods may include sampling procedures (e.g., air Methods TO-15 and 26, 

solid waste Method 5035A), validation of field procedures is not explicitly addressed in this 

guidance. 

Much of the information provided may be useful for validating other types of analytical 

methods such as empirical, qualitative, or field procedures. However, these types of methods will 

have unique considerations that will require slightly different validation approaches from those 

presented in this document. 

1.4 Terminology 

Scientific terms and meanings change with time. For many years, national and international 

standards organizations have attempted to harmonize terminology within scientific disciplines. For 

the purpose of this guidance, a glossary of terms and definitions is included in Section 9. The entries 

were compiled from current, authoritative sources, and references are included. 

Rational and empirical methods of analysis are defined and discussed in an IUPAC technical report by 

Thompson et al. The report was published in Pure & Applied Chemistry, Vol. 71, No. 2, pp. 337-348, 

1999. 

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2 Planning and Initiating Method Validation Studies 

Proper planning is critical for successful method validation studies. The development of a 

chemical method of analysis may require months or years, and the formal validation phases should 

not be pursued until substantial evidence exists that a method is a good candidate for publication as 

an EPA method. EPA scientists are relied upon to determine which methods are good candidates, 

and it is not the intention of this guidance to provide acceptance criteria for new methods. 

Method development and method validation studies generally are not viewed as completely 

separate processes. Method development, often a complex iterative process, is not explicitly 

addressed in this guidance. However, there are many similarities between the types of experiments 

conducted during method development and the types of tests performed during method validation. 

Typically, an intralaboratory method validation study is initiated when a detailed procedure 

has been written, operational parameters are believed to be optimized and finalized, and no 

additional changes are anticipated. On occasion, difficulties are encountered after beginning an 

intralaboratory study, and it is necessary to troubleshoot and optimize a method. If procedural 

changes are made, and the changes may affect the method performance characteristics, then some or 

all of the performance tests may need to be repeated. 

An interlaboratory method validation study is initiated only after a successful intralaboratory 

study has been completed. Unfortunately, some method performance difficulties may only be 

revealed after initiating a multiple laboratory study, and it may be necessary to troubleshoot and 

optimize a method after conducting such a study. If procedural changes are required, the changes 

may affect the method performance characteristics and some or all aspects of an interlaboratory 

study may need to be repeated. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

3 Method Description 

3.1 Procedures Composing a Method 

The measurement process components subjected to validation should be clearly described. 

For example, a method may include procedures for laboratory subsampling, subsample preparation, 

and instrumental analysis. In this case, the method validation effort should include an evaluation of 

all three measurement process components combined. Some chemical methods of analysis also 

include procedures for sampling (e.g., methods for air analysis and for volatile organic compounds 

in soils and other solid matrices), in which case the sampling procedures should be included in the 

validation tests. In contrast, many SW-846 methods (EPA publication “Test Methods for Evaluating 

Solid Waste: Physical/Chemical Methods”) are separate procedures for sample preparation, sample 

cleanup, or instrumental analysis. The SW-846 methods may be validated and used in various 

combinations to obtain the final analytical results. In any case, the measurement process 

components validated, and the combination of procedures composing a method, must be clearly and 

completely stated. 

3.2 Method Purpose, Scope, and Applicability 

The purpose of a method (i.e., measurement objectives) and the intended use of the data must 

be clearly defined. In addition, method scope and applicability must be well defined and clearly 

described. This helps minimize misapplications by the user. Method scope and applicability 

includes the following: 

 The measurement process components validated 

 The nature of the analytes and matrices studied 

 The range of analyte levels for which the method is claimed to be suitable 

 A description of any known limitations and any assumptions upon which a method is based 

 A description of how the method and analytical parameters chosen meet the data quality 

objectives for the specific application 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

4 Method Performance Characteristics 

The purpose, scope, and applicability determine the method performance characteristics 

chosen for study. The accuracy of a method, with respect to the materials and conditions studied 

during validation, may be evaluated from the performance characteristics. The meaning of the term 

“accuracy” has changed over the years, and accuracy should be viewed as a qualitative concept 

rather than a synonym for bias (4, 5). Accuracy is defined as the closeness of agreement between a 

measured value and either a true or accepted reference value. The following excerpt from reference 

4 (pages 167-168) provides a clear explanation of the current use of the term accuracy. 

Part 1 of the international standard ISO 5725-1 on the accuracy of measurement methods and 

results defines accuracy as the closeness of agreement between a test result and the accepted 

reference value. This definition is supplemented by a note which states that the term accuracy when 

applied to a set of test results involves a combination of random components and a common 

systematic error or bias component. Accuracy is thus viewed as a characteristic of a measurement 

process consisting of precision as well as bias components. A process is considered to be accurate 

only if it is precise as well as unbiased. A measurement process that generates repeat observations 

of a characteristic which are not close enough to one another cannot generate an accurate result. In 

fact, a new word has been coined to replace the word bias. Bias is now characterized by the 

attribute “trueness.” Trueness indicates the positive aspect of a measurement process, in contrast to 

bias, which indicated a negative aspect. The old concept of accuracy has been changed to mean 

trueness. The greater the bias of a measurement process, the less true it is. The term accuracy is 

now used in a broader context which includes both precision and trueness. Many times a 

measurement result is derived as an average of repeat measurement observations rather than a single 

observation. When the result is an average, it is likely that it is close to the conventional true value 

but the repeat measurements are not close enough to one another. Such a measurement process may 

be considered to be true but not accurate, as the process is not precise. 

Based on current trends in classifying method validation study components (2), the 

performance characteristics2 that should be evaluated include, but are not limited to: 

 Selectivity 

 Instrument calibration 

 Bias/Trueness 

 Precision 

 Quantitation limits and range 

 Detection limits 

“Sensitivity” is not listed in this guidance as a method performance characteristic. The 

scientific literature reflects different meanings and uses for this term. It is used to describe a 

performance characteristic of a detector, instrument, or an analytical method. However, it is 

possible to evaluate any of these sensitivity parameters from data and information obtained by 

studying the performance characteristics listed above. 

Most performance characteristics listed in this section are also studied during method development. However, 

experiments designed for method development purposes are typically not performed under final operating 

conditions. 

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Before validating an analytical method, it is necessary to ensure that proper sample 

preservation and storage stability studies were performed during method development. Storage 

stability must investigate the stability of the analyte(s) from the time of sampling through the time of 

analysis. If an extraction is performed, the extract stability must also be investigated. Analytes may 

be lost through volatilization, sorption, chemical degradation (abiotic reactions), and microbial 

degradation. Traditionally, preservation to prevent chemical degradation is occasionally evaluated 

but preservation to prevent microbial degradation is generally ignored. Microorganisms have the 

potential to degrade target analytes and represent a significant pathway for the fate and destruction 

of organic compounds. 

4.1 Selectivity 

Selectivity refers to the ability to correctly identify the analyte(s) of interest in the presence 

of expected chemical/physical interferences. Selectivity may be evaluated by testing appropriate 

matrix blanks and fortified (spiked) matrix blanks. Matrix blanks should contain the chemical 

species, other than the analyte(s) of interest, which are reasonably expected to be present in an actual 

sample. A worst-case sample matrix should be tested, as defined in the scope of a method, during 

both intra- and interlaboratory validation studies. 

In some cases, adequate representations of matrix blanks cannot be obtained or prepared. In 

such situations, actual samples of material containing an undetermined amount of native analyte may 

need to be studied to evaluate method selectivity. This usually requires the use of multiple 

analytical procedures (e.g., sample preparation, wet-chemistry, and/or instrumental analysis 

procedures) during an intralaboratory validation study to substantiate the selectivity of the method 

being evaluated. A combination of procedures or techniques that are based on different 

measurement principles should be used. This approach increases the likelihood that interferences 

will be identified. 

Method selectivity is typically expressed qualitatively. A qualitative selectivity statement 

includes a description of known interferences, interference effects, and the nature of the analytical 

data and information that substantiates the identity of the analyte(s) in the matrix of concern (e.g., 

elemental or molecular structure data, retention times from chromatographic separations, selective 

reaction chemistry, and results from reference standards, reference materials, matrix blanks, other 

blanks, or matrix fortifications). Quantitative measures of selectivity may also be used, although 

there is no generally accepted approach for the quantitative treatment of selectivity data (2, 6). 

Therefore, the basis for quantitative selectivity measures should be thoroughly described. 

4.2 Instrument Calibration 

Instrument calibration refers to the procedures used for correlating instrument response to an 

amount of analyte (concentration or other quantity). The characteristics of a calibration function and 

justification for a selected calibration model should be demonstrated during an intralaboratory 

method validation study. 

The performance of a calibration technique and the choice of calibration model (e.g., firstorder linear, curvilinear, or nonlinear) are critical for minimizing sources of instrument bias and 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

optimizing precision. A calibration model is a mathematical function that relates composition to 

instrument response. The parameters of the model are usually estimated from the responses of 

known, pure analytes. Calibration errors can result from failure to identify the best calibration 

model; inaccurate estimates of the parameters of the model; or inadequately studied, systematic 

effects from matrix components. 

During method development and validation, calibration models are typically evaluated by 

analyzing multiple levels of calibration standards over a selected working range. Measurements 

should be replicated at each calibrant level to evaluate the random error associated with instrument 

response, and to evaluate goodness-of-fit for various linear, curvilinear, or non-linear models. For 

example, if a method states that an average response factor may be used for calibration over a 

specified analyte range, then the instrument response should be demonstrated, during intralaboratory 

method validation, to be a first-order linear equation, and that the y-intercept is zero within error. 

The calibration study results should be included in a method validation report. Access to 

information about calibration performance characteristics assists the user in implementing new 

methods and verifying that a laboratory’s instrument performance is acceptable. 

As mentioned above, the calibration approach stated in a method should be thoroughly tested 

and justified during an intralaboratory validation study, and tested according to the 

required/recommended calibration procedure during an interlaboratory validation study. For 

example, an intralaboratory study may include several calibration standards and replicate readings of 

each standard. If the calibration performance characteristics are deemed acceptable, the 

required/recommended calibration approach may include the use of only three calibration standards, 

single readings of each standard, and the calculation of an average response factor. In this case, the 

interlaboratory study would involve the use of an average response factor as opposed to the full 

calibration approach used during the intralaboratory study. In any case, the instrument calibration 

procedure used in the final EPA method should be thoroughly studied, justified, and documented in 

a method validation report. 

4.3 Bias/Trueness 

Bias refers to the overall magnitude of known systematic (determinate) errors associated with 

the use of an analytical method. The presence of systematic errors can only be determined by 

comparison of the average of many results with a reliable, accepted reference value. Method bias 

may be estimated by measuring materials whose composition is reasonably well known, such as 

reference materials, by comparing results to those from at least one alternate method or procedure, or 

by analyzing spiked materials. 

The relationship between the terms bias and trueness is clearly described in ISO 5725-1 (5). 

Two excerpts from this document are as follows: 

The “trueness” of a measurement method is of interest when it is possible to conceive of a true 

value for the property being measured. Although, for some measurement methods, the true value 

cannot be known exactly, it may be possible to have an accepted reference value for the property 

being measured; for example, if suitable reference materials are available, or if the accepted 

reference value can be established by reference to another measurement method or by preparation 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

of a known sample. The trueness of the measurement method can be investigated by comparing the 

accepted reference value with the level of the results given by the measurement method. Trueness 

is normally expressed in terms of bias. Bias can arise, for example, in chemical analysis if the 

measurement method fails to extract all of an element, or if the presence of one element interferes 

with the determination of another. 

The term bias has been in use for statistical matters for a very long time, but because it caused 

certain philosophical objections among members of some professions (such as medical and legal 

practitioners), the positive aspect has been emphasized by the invention of the term trueness. 

It should be noted that all approaches for evaluating trueness have limitations. Examples of 

these limitations are as follows: 

• The reference materials approach introduces the important uncertainty of matrix 

matching, and the reliability of a bias estimate depends upon the relationship between 

the composition of the reference material and the samples. 

• When using the alternate method approach, the reliability of a bias estimate is 

dependent upon how much is known about the performance characteristics of the 

alternate method. 

• The matrix spiking approach introduces uncertainty regarding the behavior of spiked 

materials, compared to materials containing native analyte. This may be particularly 

problematic for solid materials. 

Rigorous evaluations of trueness should be included in EPA method validation studies. 

Minimally, trueness should be evaluated at the extremes of the quantitation range stated in the scope 

of a method, and at regulatory levels. 

4.4 Precision 

The general term “precision” is used to describe the magnitude of random (indeterminate) 

errors associated with the use of an analytical method. The sources of random error evaluated 

depend upon the range of conditions over which the data are collected. The following definitions are 

recommended (7). 

 Repeatability (of results of measurements) - closeness of agreement between the results of 

successive measurements of the same measurand carried out under the same conditions of 

measurement. These conditions are called repeatability conditions. Repeatability conditions 

include the same measurement procedure, observer, measuring instrument (used under the 

same conditions), location, (and) repetition over a short period of time. Repeatability may be 

expressed quantitatively in terms of the dispersion characteristics of the results. 

 Reproducibility (of results of measurements) - closeness of agreement between the results of 

measurements of the same measurand carried out under changed conditions of measurement. 

A valid statement of reproducibility requires specification of the conditions changed. The 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

changed conditions may include principle of measurement, method of measurement, 

observer, measuring instrument, reference standard, location, conditions of use, (and) time. 

Reproducibility may be expressed quantitatively in terms of the dispersion characteristics of 

the results. 

Minimally, method repeatability and reproducibility should be evaluated at the extremes of 

the quantitation range stated in the scope of a method, and must be evaluated at regulatory levels. 

(The quantitation range must include regulatory levels; see section 4.5.) Common measures of 

dispersion are the standard deviation and relative standard deviation of repeated measurements. The 

repeatability and reproducibility conditions should be clearly stated so that the measures of 

dispersion can be properly interpreted and evaluated. 

Precision and trueness evaluations, known as accuracy studies, are often performed 

concurrently. A variety of test materials may be used for these studies, and the effects of laboratory 

subsampling should be included when appropriate. 

4.5 Quantitation Limits and Range 

The term “quantitation range” is used to describe the span of analyte levels, as contained in a 

sample matrix, for which method performance has been tested, and data quality is deemed 

acceptable for its intended use. A quantitation range must include either a regulatory or other type 

of action level. 

A lower limit and an upper limit bound a quantitation range. A quantitation range may be 

wider than an instrument’s calibration range because of dilution or concentration steps performed 

during sample preparation. Dilution factors or concentration factors are used to relate the calibration 

range to the quantitation range. Analyte concentration will have an effect on most method 

performance characteristics, including trueness and precision. At a minimum, method trueness and 

precision (as described in sections 4.3 and 4.4) should be evaluated at the extremes of the 

quantitation range. 

The lower limit of the quantitation range is commonly referred to as the “limit of 

quantitation” or LOQ. There are numerous definitions in the scientific literature for this limit, and 

no single definition is appropriate for all EPA chemical methods of analysis. Defined limits, such as 

those based on specifications for precision, should be verified by testing materials containing analyte 

at the claimed LOQ. 

4.6 Detection Limit(s) 

The term “detection limit” is used to describe the lowest analyte level that can be confidently 

identified. There are many specific definitions for this term, and it is used to describe the detection 

capabilities of detectors, instruments, and analytical methods. The term “detection limit” must be 

defined, and a description of how it was evaluated during method validation must be provided. 

Limits derived from mathematical definitions or statistical models must be verified by testing 

materials containing analyte at the claimed detection level. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

5 Ruggedness Testing 

Ruggedness refers to the extent to which an analytical method remains unaffected by minor 

variations in operating conditions. Ruggedness testing involves experimental designs for examining 

method performance when minor changes are made in operating or environmental conditions. The 

changes should reflect expected, reasonable variations that are likely to be encountered in different 

laboratories. 

A commonly used, efficient approach for a ruggedness test is based on a fractional factorial 

experimental design3 (8, 9, 10). This approach is more efficient than varying conditions one at a 

time. Various types of precision studies may also reveal the effects of some influential factors. 

Analyst observations are also important, and may reveal critical control points that should be 

documented in a method. 

Ruggedness testing may be conducted at the end of a method development effort, or during 

an intralaboratory study. Regardless of timing, ruggedness testing should be completed before 

initiating an interlaboratory method validation study, and critical control points should be identified 

in the documented method. 

The fractional factorial experimental design referenced herein is not intended for method optimization 

purposes. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

6 Interlaboratory Studies 

Interlaboratory studies determine whether an analytical method can be transferred for use in 

other laboratories and used for regulatory testing. A method that proved rugged for use in one 

laboratory may lose that characteristic when tried in several other laboratories. Therefore, an 

interlaboratory method validation study should be completed prior to publishing an EPA method for 

general use. The extent of the study will vary depending on available resources and the intended use 

and applicability of the method. These studies are resource intensive, and should not be initiated 

until a successful intralaboratory study has been completed and the issuing entity has demonstrated a 

pressing programmatic need for publishing a national method. 

An interlaboratory method validation study is a practical testing of the written method on 

identical materials, usually derived from split samples, by a number of laboratories. The study is not 

intended to evaluate laboratories; it is intended to evaluate method reproducibility among 

laboratories. Deviations from the interlaboratory study protocol should be strongly discouraged, and 

any deviations that occur should be documented. 

There are several excellent references for the design and conduct of interlaboratory method 

validation studies. Three such references are listed in section 10 of this document (11, 12, 13). 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

7 Method Validation Reports 

A method validation report, suitable for placing in the public docket, should be prepared. 

The report should address the method validation topics outlined in this guidance document 

(summarized in Table 1), and (a) background information on method development, (b) a description 

of the actual method validation techniques, (c) any changes made to the method as a result of the 

validation studies, and (d) any recommendations for future work 

Table 1 

Method Validation Report Topic Areas 

Topic Explanation 

Purpose The purpose of the method is a clear and concise description of the measurement objectives and the intended use 

of the data. 

Scope and 

Applicability 

The method scope and applicability serve to define the range of method performance studies. The scope and 

applicability includes (a) the measurement process components validated, (b) the nature of the analytes and 

matrices studied, (c) the range of analyte levels for which the method is claimed to be suitable, (d) a description 

of any known limitations and any assumptions upon which a method is based, and (e) a description of how the 

method and analytical parameters chosen meet the data quality objectives for the specific application. 

Selectivity 

Selectivity is a performance characteristic that demonstrates the ability of the method to yield useful data for the 

analytes, analyte levels, and matrices defined within the scope of the method. Selectivity is especially important 

at action levels of concern, and must be demonstrated in the presence of species known or predicted to present 

analytical challenges to the method. Typically, selectivity is demonstrated by providing information that 

substantiates the identity of the analytes in the presence of expected matrix constituents. 

Instrument 

Calibration 

This performance characteristic is sometimes referred to as “instrument linearity.” In a broader sense, it 

addresses instrument calibration and the nature of the resulting calibration model. During method validation, 

sufficient data should be generated to demonstrate and justify the method-recommended calibration approach. 

Bias/Trueness 

Trueness is a performance characteristic that addresses sources of known systematic error, and bias is a measure 

of trueness. The extent of bias in a measurement process typically varies with analyte, analyte level, and matrix. 

Therefore, trueness should be evaluated using samples that span the degree of analytical difficulty encompassed 

by the specified scope and applicability. Examples of approaches used to assess trueness include the use of 

reference materials, alternate methods or techniques, and matrix fortification. 

Precision 

(Repeatability and 

Reproducibility) 

Precision is a performance characteristic that reflects sources of random error in a measurement process. There 

are several different types of precision studies (i.e., repeatability and reproducibility studies). Methods designed 

for demonstrating compliance with regulatory requirements should be evaluated for both repeatability (withinlab) and reproducibility (among labs). 

Quantitation Range 

and Limits 

A quantitation range corresponds to the range of analyte concentrations (or other quantity) characterized for 

measurement accuracy (trueness and precision) during method validation. Analytical measurement uncertainty 

should be well characterized over a quantitation range. 

Detection Limits 

This general term describes the lowest level of analyte that can be identified with confidence. A method 

validation study typically involves a specific detection limit definition, and includes an explanation of how the 

defined detection limit was estimated. Detection limit estimates derived from mathematical definitions or 

statistics must be verified by analyzing samples containing analyte at the claimed detection level. This 

performance characteristic may not be important for all analytical applications, and its relevance depends on the 

method scope and applicability. 

Ruggedness 

Ruggedness refers to the capacity of an analytical method to remain unaffected by small variations in operating 

conditions. Ruggedness testing involves experimental designs for examining method performance when small 

changes are made in operating or environmental conditions. The changes should reflect expected, reasonable 

variations that are likely to be encountered in different laboratories. 

Interlaboratory 

Study 

Interlaboratory studies determine whether an analytical method can be transferred for use in other laboratories 

and used for regulatory testing. The design and results of the interlaboratory study should be included in the 

method validation summary report. Data from the interlaboratory study should be reported in tabular form. 

There should also be a discussion included describing the details of, and rationale for, any changes made to the 

method resulting from the interlaboratory study. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

8 Peer Review 

Before publication, EPA methods of analysis are peer reviewed in accordance with the 

information provided in the most current version of the EPA Science Policy Council Peer Review 

Handbook (3). The Peer Review Handbook provides Agency-wide guidance for the consistent 

implementation of peer review, and Program Offices have the flexibility to design peer reviews to 

suit their specific needs. The Handbook is the source of detailed information about which Agency 

work products are subject to peer review. In addition, there is information about selecting peer 

review mechanisms (internal and external), planning a peer review process, conducting a peer 

review, and preparing a peer review record. Each EPA office has a Peer Review Coordinator 

available for assistance. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

9 Terms and Definitions 

Terms and definitions were obtained from the following authoritative sources: 

 American National Standards Specification and Guidelines for Quality Systems for 

Environmental Technology Programs, Annex A (2004) (ANSI/ASQ) 

 International Vocabulary of Basic and General Terms in Metrology, 2nd Edition, 

International Organization for Standardization (1993) (VIM) 

 Accuracy (trueness and precision) of measurement methods and results – Part 1: General 

principles and definitions, International Organization for Standardization, ISO 5725-1, 

1994-12-15 (ISO 5725-1) 

For each term and definition, the specific reference is indicated in parentheses. Numbers identifying 

VIM terms and definitions are also included. The numbering of the notes from ISO 5725-1 is the 

same as the numbering in the original ISO document. 

accepted reference value: A value that serves as an agreed up reference for comparison, and which 

is derived as: 

a) a theoretical or established value, based on scientific principles; 

b) an assigned or certified value, based on experimental work of some national or international 

organization; 

c) a consensus or certified value, based on collaborative experimental work under the auspices 

of a scientific or engineering group; 

d) when a), b) and c) are not available, the expectation of the (measurable) quantity, i.e. the 

mean of a specified population of measurements. (ISO 5725-1) 

accuracy: The closeness of agreement between a test result and the accepted reference value. (ISO 

5725-1) 

NOTE 2 The term accuracy, when applied to a set of test results, involves a combination of random 

components and a common systematic error or bias component. 

accuracy of measurement: closeness of the agreement between the result of a measurement and a 

true value of the measurand (VIM 3.5) 

NOTES 

1 “Accuracy” is a qualitative concept. 

2 The term precision should not be used for “accuracy”. 

bias: The difference between the expectation of the test results and an accepted reference value. 

(ISO 5725-1) 

NOTE 5 Bias is the total systematic error as contrasted to random error. There may be one or more 

systematic error components contributing to the bias. A larger systematic difference from the 

accepted reference value is reflected by a larger bias value. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

calibration: set of operations that establishes, under specified conditions, the relationship between 

values of quantities indicated by a measuring instrument or measuring system, or values represented 

by a material measure or a reference material, and the corresponding values realized by standards 

(VIM 6.11) 

NOTES 

1 The result of a calibration permits either the assignment of values of measurands to the 

indications or the determination of corrections with respect to indications. 

2 A calibration may also determine other metrological properties such as the effect of influence 

quantities. 

3 The result of a calibration may be recorded in a document, sometimes called a calibration 

certificate or a calibration report. 

measurand: particular quantity subject to measurement (VIM 2.6) 

EXAMPLE vapour pressure of a given sample of water at 20 °C. 

NOTE The specification of a measurand may require statements about quantities such as 

time, temperature and pressure. 

measurement procedure: set of operations, described specifically, used in the performance of 

particular measurements according to a given method (VIM 2.5) 

NOTE A measurement procedure is usually recorded in a document that is sometimes itself called 

a “measurement procedure” (or a measurement method) and is usually in sufficient detail 

to enable an operator to carry out a measurement without additional information. 

method: A body of procedures and techniques for performing an activity (e.g., sampling, chemical 

analysis, quantification) systematically presented in the order in which they are to be executed. 

(ANSI/ASQ) 

precision: The closeness of agreement between independent test results obtained under stipulated 

conditions. (ISO 5725-1) 

NOTES 

9 Precision depends only on the distribution of random errors and does not relate to the true 

value or the specified value. 

10 The measure of precision is usually expressed in terms of imprecision and computed as a 

standard deviation of the test results. Less precision is reflected by a larger standard 

deviation. 

11 “Independent test results” means results obtained in a manner not influenced by any previous 

result on the same or similar test object. Quantitative measures of precision depend critically 

on the stipulated conditions. Repeatability and reproducibility conditions are particular sets 

of extreme conditions. 

procedure: A specified way to carry out an activity or process. (ANSI/ASQ) 

random error: result of a measurement minus the mean that would result from an infinite number 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

of measurements of the same measurand carried out under repeatability conditions (VIM 3.13) 

NOTES 

1 Random error is equal to error minus systematic error. 

2 Because only a finite number of measurements can be made, it is possible to determine 

only an estimate of random error. 

repeatability (of results of measurements): closeness of the agreement between the results of 

successive measurements of the same measurand carried out under the same conditions of 

measurement (VIM 3.6) 

NOTES 

1 These conditions are called repeatability conditions.

2 Repeatability conditions include: 

- the same measurement procedure 

- the same observer 

- the same measuring instrument, used under the same conditions 

- the same location 

- repetition over a short period of time. 

3 Repeatability may be expressed quantitatively in terms of the dispersion characteristics of the 

results. 

reproducibility (of results of measurements): closeness of the agreement between the results of 

measurements of the same measurand carried out under changed conditions of measurement. (VIM 

3.7) 

NOTES 

1 A valid statement of reproducibility requires specification of the conditions changed. 

2 The changed conditions may include: 

- principal of measurement 

- method of measurement 

- observer 

- measuring instrument 

- reference standard 

- location 

- conditions of use 

- time. 

3 Reproducibility may be expressed quantitatively in terms of the dispersion characteristics of

 the results. 

4 Results are here usually understood to be corrected results. 

result of a measurement: value attributed to a measurand, obtained by measurement (VIM 3.1) 

NOTES 

1 When a result is given, it should be made clear whether it refers to: 

- the indication 

- the uncorrected result 

- the corrected result

and whether several values are averaged.

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

2 A complete statement of the result of a measurement includes information about the uncertainty

 of measurement. 

systematic error: mean that would result from an infinite number of measurements of the same 

measurand carried out under repeatability conditions minus a true value of the measurand (VIM 

3.14) 

NOTES 

1 Systematic error is equal to error minus random error. 

2 Like true value, systematic error and its causes cannot be completely known. 

3 For a measuring instrument, see “bias” (VIM 5.25). 

true value (of a quantity): value consistent with the definition of a particular quantity (VIM 1.19) 

NOTES 

1 This is a value that would be obtained by a perfect measurement. 

2 True values are by nature indeterminate. 

3 The indefinite article “a”, rather than definite article “the”, is used in conjunction with “true 

value” because there may be many values consistent with the definition of a given particular 

quantity. 

trueness: The closeness of agreement between the average value obtained from a large series of test 

results and an accepted reference value. (ISO 5725-1) 

NOTES 

3 The measure of trueness is usually expressed in terms of bias. 

4 Trueness has been referred to as “accuracy of the mean”. This usage is not recommended. 

uncertainty of measurement: parameter, associated with the result of a measurement, that 

characterizes the dispersion of the values that could reasonably be attributed to the measurand (VIM 

3.9) 

NOTES 

1 The parameter may be, for example, a standard deviation (or a given multiple of it), or 

the half-width of an interval having a stated level of confidence. 

2 Uncertainty of measurement comprises, in general, many components. Some of these 

components may be elevated from the statistical distribution of the results of series of 

measurements and can be characterized by experimental standard deviations. The 

other components, which can be characterized by standard deviations, are evaluated 

from assumed probability distributions based on experience or other information. 

3 It is understood that the results of the measurement is the best estimate of the value of the 

measurand, and that all components of uncertainty, including those arising from systematic 

effects, such as components associated with corrections and reference standards, contribute 

to the dispersion. 

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Validation and Peer Review of U.S. EPA Chemical Methods of Analysis October 14, 2005 

10 References 

1. Eurachem. The Fitness for Purpose of Analytical Methods: A Laboratory Guide to 

Method Validation and Related Topics; LGC (Teddington) Ltd.: Middlesex, United 

Kingdom, 1998. (ISBN 0-94892-612-0) 

2. Thompson, M.; Ellison, S.L.R.; Wood, R. Harmonized guidelines for single-laboratory 

validation of methods of analysis, IUPAC Technical Report. Pure Appl. Chem. 2002, 74 (5), 

835-855. 

3. EPA Science Policy Council Peer Review Handbook, 2nd ed.; EPA 100-B-00-001; US 

Environmental Protection Agency, Office of Science Policy, Office of Research and 

Development, Washington, DC, December 2000. 

4. Kimothi, S.K. The Uncertainty of Measurements; ASQ Quality Press: Milwaukee, WI, 2002. 

 (ISBN 0-87389-535-5) 

5. International Organization for Standardization (ISO). Accuracy (trueness and precision) of 

measurement methods and results - Part 1: General principles and definitions; ISO 5725-1: 

1994(E), Geneva, Switzerland, 1994. 

6. Vessman, J.; Stefan, R.; van Standen, J.; Danzer, K.; Lindner, W.; Burns, D.; Fajgelj, A.; 

Muller, H. Selectivity in Analytical Chemistry, Pure Appl. Chem. 2001, 73(8), 1381-1386. 

7. International Organization for Standardization (ISO). International Vocabulary of Basic and 

General Terms in Metrology (VIM), 2nd ed., Geneva, Switzerland, 1993. 

8. ASTM E 1169-02. Standard Guide for Conducting Ruggedness Tests; Annu. Book of 

 ASTM Stand. 2003, (14.02), 318-324. 

9. Youden, W.J.; Steiner, E.H. Statistical Manual of the AOAC; AOAC: Arlington, VA, 

1975. (Fifth printing 1987; ISBN 0-935584-15-3) 

10. Wernimont, G. Use Of Statistics To Develop And Evaluate Analytical Methods; AOAC: 

Arlington, VA, 1985. (Fourth printing 1993; ISBN 0-935584-31-5) 

11. AOAC International. AOAC®Official MethodsSM Program Manual (OMA Program 

Manual, Part 6, Appendix D: Guidelines for Collaborative Study Procedures to Validate 

Characteristics of a Method of Analysis; Gaithersburg, MD, 2002. 

12. Horwitz, W. Protocol for the design, conduct and interpretation of method 

performance studies: Revised 1994 (Technical Report), Pure Appl. Chem. 1995, (67), 

332-343. 

13. ASTM E 691-99. Standard Practice for Conducting an Interlaboratory Study to Determine 

the Precision of a Test Method, Annu. Book of ASTM Stand. 2003, (14.02), 203-224. 

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