semi合集-English.pdf - 第6609页

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8 4.28 14 3.64 20 3.42
9 4.09 15 3.59
6.3.3.2 Such analyses should be performed by using a spreadsheet or computer program. It is not recommended to
do them by hand. The previous equations neither require nor prevent use of data from blank quantification. In order
to use blank data in the MDL quantification with OLS, the blank should be measurable, be likely to give a response
which is consistent with the pattern in the other calibration data, and provide a similar level of variability to that
obtained from the investigated standards.
6.3.4 Calculations — WLS and Linear Calibration Model
6.3.4.1 A line which is not constrained to pass through the origin is used as the calibration model. WLS is used to
estimate the model in which the weights are determined as a function of the observed variability at each
concentration level. The MDL is located by determining the 3 sigma equivalent Upper Confidence Limit at X = 0
and using a linear calibration model to convert this result into the corresponding concentration (MDL). While many
of the WLS analysis quantity names are identical to those in the OLS analysis (e.g.,
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SEMI C10-0305 © SEMI 1998, 2005 6
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6.3.4.2 Since some calculations, for example that of s, may lead to computation of a relatively small difference
between two relatively large numbers; it is critical that all previous calculations not be based on rounded numbers.
In general, such analyses should be performed using a spreadsheet or computer program.
6.3.4.3 The previous equations neither require nor prevent use of data from blank quantification. In order to use
blank data in the MDL quantification with WLS, the blank should be measurable, be likely to give a response which
is consistent with the pattern in the other calibration data, and provide a level of variability consistent with the
pattern seen in the investigated standards.
6.3.5 Alternative Calculations — Situations exist for which both prior alternatives (¶6.3.3 and ¶6.3.4) may be
inappropriate. For example:
(a) a calibration model may be nonlinear,
(b) a calibration model may be multivariate in nature,
(c) the implicit assumption of normality of residuals (errors in predictions about the calibration) may not be an
appropriate distributional assumption,
(d) the lowest level standard used in calibration may be too far above the true MDL.
6.3.5.1 In case (a), a nonlinear model can be used instead of the default linear model in performing a regression
analysis which quantifies the Upper Confidence Limit for individuals at X = 0 at a 3 sigma equivalent probability
level (and back-projects this result through the nonlinear calibration model to estimate the MDL). How to
accomplish this is the responsibility of those applying this alternative. In some situations, a transformation of scale
(X and/or Y) may linearize the model such that the previously provided calculations are again applicable.