1. Accuracy without error; closeness to the true value
2. Analytical
Measurement
Range (AMR)
Also known as linear or dynamic range.
Range of analyte concentrations that can be
directly measured without dilution,
concentration, or other
Pretreatment
3. Bias systematic discrepancy between a
measurement and the true value; may be
constant or proportionate and may adversely
affect test results; the difference between the
observed mean and the reference mean.
Negative bias indicates that the test values
tend to be lower than the reference value,
whereas positive bias indicates test values are
generally higher. Bias is a type of constant
systematic error
4. Clinical
Laboratory
Improvement
Amendment
(CLIA)
regulations signed into federal law in 1988;
mandate standards in clinical laboratory
operations and testing
5. Clinically
Reportable
Range (CRR )
range of analyte that a method can
quantitatively report, allowing for dilution,
concentration, or other pretreatment used to
extend AMR
6. Confidence
Interval
Range of values that include a specified
probability, usually 90% or 95%. For example,
consider a 95% confidence interval for slope =
0.972 - 0.988 from a method comparison
experiment. If this same experiment were
conducted 100 times, then the slope would
fall between 0.9772 and 0.988 in 95 of the 100
times. Confidence intervals serve to convey
the variability of estimates and quantify the
variability
7. Constant
Error
a type of systemic error in the sample
direction and magnitude; the magnitude of
change is constant and not dependent on the
amount of analyte
8. Control a substance or material of determined value,
used to monitor the accuracy and precision of
a test. Controls are run with the patient's
specimens
9. Control Limit Threshold at which the value is statistically
unlikely
10. Descriptive
Statistic
statistics or values (e.g., mean, median, and
mode) used to summarize the important
features of a group of data; analysis of a data
set that helps describe, show or summarize
data in a meaningful way such that, for
example, patterns might emerge from the data
11. Dispersion the spread of data; most simply estimated by
the range, the difference between the largest
and smallest observations. The most
commonly used statistic for describing the
dispersion of groups of single observations is
the standard deviation, which is usually
represented by the symbol s
12. Histogram graphical representation of data where the
number or frequency of each result is placed
on the y-axis and the value of the result is
plotted on the x-axis
13. Imprecision Dispersion of repeated measurements about
the mean due to analytic error
14. Inaccuracy Difference between a measured value and its
true value due to systematic error, which can
be either constant or proportional error
15. Inferential
Statistics
values or statistics used to compare the
features of two or more groups of data;
techniques that allow us to use representative
samples to make generalizations (inferences,
probabilities) about the populations from which
the samples were drawn
16. Levy-
Jennings
Control
Chart
a chart illustrating the allowable limits of error
in laboratory test performance, the limits being
a defined deviation from the mean of a control
serum,most commonly +/-2 s tandard deviations
17. Limit of
Dete ction
(LoD)
Lowest amount of analyte accurately detected
by a method
18. Linear
Regression
statistical calculations of the slope (b), the y
intercept (a), and the standard deviation of the
points about the regression line (sy/x), and the
correlation coefficient (r) to compare two
methods
19. Multirule
Procedure
Decision criteria to determine if an analytic run
is in control; used to detect random and
systematic error over time
20. Negative
Predictive
Value
Chance an individual does not have a given
disease or condition if the test is within the
reference interval; NPV = TN/(TN + FN) × 100
Chapter 3 Terms
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