ASTM F2340-05

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Designation: F2340 – 05
Standard Specification for
Developing and Validating Prediction Equation(s) or
Model(s) Used in Connection with Livestock, Meat, and
Poultry Evaluation Device(s) or System(s) to Determine
1
Value
This standard is issued under the fixed designation F2340; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision.Anumber in parentheses indicates the year of last reapproval.A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope 3.2.3 coeffıcient of determination, n—percentage of vari-
ability in the response (dependent) variable that can be
1.1 Thisspecificationcoversmethodstocollectandanalyze
explained by the prediction equation.
data, document the results, and make predictions by any
2
objectivemethodforanycharacteristicusedtodeterminevalue
~y 2 yˆ!
(
2
R 51–
2
in any species using livestock, meat, and poultry evaluation
~y 2 y !
(
devices or systems.
3.2.4 root mean square error for calibration, n—squareroot
1.2 This standard does not purport to address all of the
of the sum of squared residuals divided by n −(k+1), where
c
safety concerns, if any, associated with its use. It is the
n is the sample size for the calibration data set, and k is the
c
responsibility of the user of this standard to establish appro-
number of explanatory variables in the prediction equation.
priate safety and health practices and determine the applica-
2
bility of regulatory requirements prior to use.
~y 2 yˆ!
(
Œ
n 2 ~k 11!
c
2. Referenced Documents
3.2.5 root mean square error for validation, n—square root
2
2.1 ASTM Standards:
of the sum of squared residuals divided by n , where n is the
y y
F2463 Terminology for Livestock, Meat, and Poultry
sample size for the validation data set.
Evaluation Systems
2
~y 2 yˆ!
(
Œ
3. Terminology
n
v
3.1 For definitions of terms used in this specification, refer
3.2.6 validation data set, n—the data set used to test the
to Terminology F2463.
predictive accuracy of the equations developed from the
3.2 Definitions of Terms Specific to This Standard:
calibration data set.
3.2.1 accuracy, n—statement of the exactness with which a
3.2.7 value, commerce, n—measure of economic worth in
measurement approaches the true measure for that character-
commerce.
istic;accuracyiscontrastedwithprecision,whichisconcerned
with the repeatability of the measurements. Therefore, with a 4. Significance and Use
largebias,ameasurementmaybeofhighprecision,butoflow
4.1 Theproceduresinthisspecificationaretobeusedbyall
accuracy.
parties interested in predicting composition or quality, or both,
3.2.2 calibration data set, n—data set used to develop the
for the purpose of establishing value based upon device or
initial prediction equations; same as developmental or predic-
system measurements.Whenever new prediction equations are
tion data set.
established, or when a change is experienced that could affect
the performance of existing equations, these procedures shall
be used.
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This specification is under the jurisdiction of ASTM Committee F10 on
Livestock, Meat, and Poultry Evaluation Systems and is the direct responsibility of
5. Procedure
Subcommittee F10.40 on Predictive Accuracy.
Current edition approved Dec. 1, 2005. Published December 2005. Originally
5.1 Experimental Design:
approved in 2004. Last previous edition approved in 2004 as F2340–04. DOI:
5.1.1 Define the Population for Development of a Prediction
10.1520/F2340-05.
2
For referenced ASTM standards, visit the ASTM website, www.astm.org, or Equation:
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
Standards volume information, refer to the standard’s Document Summary page on
the ASTM website.
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F2340 – 05
5.1.1.1 To establish the predictive ability and validity of an able methods, should be used to obtain the measurements
equation(s) using measures (independent variables) from an underthesameconditionsinwhichthedeviceorsystemwould
evaluation device or system, it is necessary to define the be expected to operate. In particular, the validity of the
population on which the prediction model is intended to be approach and the repeatability of the procedure must be
used. documented and demonstrated. For many of the common
(1)Thespeciesonwhichmeasurementswillbemademust characteristics to be predicted (such as percent lean), there are
be defined. a number of reference methods commonly accepted within the
(2)Thepopulationforscopeofusemustbeclearlydefined. discipline.Where accepted methods exist, they should be used
This may include, but is not limited to, factors such
...