The are numerous models that describe the relationship between the variance and measured quantity value across the measuring interval:
| Fit | Description |
|---|---|
| Constant variance | Fit constant variance across the measuring interval. |
| Constant CV | Fit constant coefficient of variation across the measuring interval. |
| Mixed constant / proportional variance | Fit constant variance at low levels with constant coefficient of variation at high levels. |
| 2-parameter | Fir a 2-parameter linear variance function. |
| 3-parameter | Fit Sadler 3-parameter variance function – a monotone relationship (either increasing or decreasing) between the variance and level of measurement. |
| 3-parameter alternative | Fit Sadler alternate 3-parameter variance function – gives more flexibility than the Sadler standard 3-parameter variance function especially near zero. |
| 4-parameter | Fit a Sadler 4-parameter variance function - allows for a turning point near the detection limit. |
A variance function can be useful to estimate the limit of detection or limit of quantitation.
From the Statistical Reference Guide for Analyse-it 6.24.0: https://analyse-it.com/docs/user-guide/measurement-systems-analysis/precision/variance-function
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