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JMP(R) Software: Analysis of Dose-Response Curves

This course helps you fit a sigmoid model to your dose-response curve data, select the best model, assess the model fit, determine whether two curves are parallel, determine the EC50 or relative...

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$725 USD GSA  $589.42
Course Code JDOS14
Duration 1 day
Available Formats Classroom
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This course helps you fit a sigmoid model to your dose-response curve data, select the best model, assess the model fit, determine whether two curves are parallel, determine the EC50 or relative potency, and optimize the doses and assay replication for the reference standard curve. This course uses JMP 14.

Skills Gained

  • Distinguish between linear and nonlinear models of data.
  • Describe the important characteristics of a good model of dose-response data.
  • Identify features of the model (parameters) that relate to the shape of the dose-response curve.
  • Control the nonlinear fitting process.
  • Decide whether and how to weight the response.
  • Use criteria to select a model from a library of logistic functions.
  • Set up nonlinear regression for custom models.

Who Can Benefit

  • Directors, managers, engineers, scientists, technicians, and analysts who work with assays that are based on a dose-response curve

Prerequisites

  • Before attending this course, it is recommended that you do the following:
  • Complete the JMP® Software: A Case Study Approach to Data Exploration course or have equivalent experience.
  • Complete the JMP®: Statistical Decisions Using ANOVA and Regression course or have equivalent experience.

Course Details

Modeling Dose-Response Curves

  • Comparing linear and nonlinear models.
  • Common models for dose-response curves.
  • Fitting dose-response models.
  • Fitting custom dose-response models.

Exploiting Dose-Response Models

  • Validating the model: parallel curves.
  • Determining relative potency.

Design for Nonlinear Models

  • Optimal data collection.
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