Module: IC50 Curves
(Logistic Regression)
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| Lesson Objective | Learn how to calculate best fit curves for concentration or dose–response plots using logistic regression (the Hill equation) |
| Section | Description |
| Concentration or Dose-Response Plots | A discussion of expected data format, and a brief review of the process for creating a semi-log scatter plot which is trellised by compound. |
| Logistic Regression Calculation | A detailed discussion of the logistic regression algorithm (Hill equation) and definition of the X50 value. |
| Adding the Logistic Regression Curve Fit | How to add a dose-response curve fit, based on all records or selected records, the option to define fixed min and max values, and forcing separate calculations for individual trellis panels. |
| Results (IC50, EC50, or ED50 values |
How to view the Equation, Correlation coefficient, Slope, Max and Min, and X50 values. Information available in the Legend vs. the detailed Results window. Examples of messages reported when calculation difficulties are encountered. |
| Adding More Than One Curve (Evaluating Bad Data Points) | The discussion of a suggested stepwise approach to evaluating the effect of bad data points on your IC50 curves. |
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