Fitting Models to Biological Data Using Linear and Nonlinear Regression A Practical Guide to Curve Fitting 1st Edition by Harvey Motulsky, Arthur Christopoulos 0195171802 9780195171808

An Example of Nonlinear Regression

Preparing Data for Nonlinear Regression

Nonlinear Regression Choices

The First Five Questions to Ask About Nonlinear Regression Results

The Results of Nonlinear Regression

Troubleshooting “Bad” Fits

Choosing Linear Regression

Interpreting the Results of Linear Regression

Introducing Models

Tips on Choosing a Model

Global Models

Compartmental Models and Defining a Model with a Differential Equation

Modeling Experimental Error

Unequal Weighting of Data Points

How Nonlinear Regression Minimizes the Sum-of-Squares

Asymptotic Standard Errors and Confidence Intervals

Generating Confidence Intervals by Monte Carlo Simulations

Generating Confidence Intervals via Model Comparison

Comparing the Three Methods for Creating Confidence Intervals

Using Simulations to Understand Confidence Intervals and Plan Experiments

Approach to Comparing Models

Comparing Models Using the Extra Sum-of-Squares F Test

Comparing Models Using Akaike’s Information Criterion (AIC)

How Should You Compare Models — AICc or F Test?

Examples of Comparing the Fit of Two Models to One Data Set

Testing Whether a Parameter Differs from a Hypothetical Value

Using Global Fitting to Test a Treatment Effect in One Experiment

Using Two-Way ANOVA to Compare Curves

Using a Paired t Test to Test for a Treatment Effect in a Series of Matched Experiments

Using Global Fitting to Test for a Treatment Effect in a Series of Matched Experiments

Using an Unpaired t Test to Test for a Treatment Effect in a Series of Unmatched Experiments

Using Global Fitting to Test for a Treatment Effect in a Series of Unmatched Experiments

The Law of Mass Action

Analyzing Radioligand Binding Data

Calculations with Radioactivity

Analyzing Saturation Radioligand Binding Data

Analyzing Competitive Binding Data

Homologous Competitive Binding Curves

Analyzing Kinetic Binding Data

Analyzing Enzyme Kinetic Data

Introduction to Dose-Response Curves

The Operational Model of Agonist Action

Dose-Response Curves in the Presence of Antagonists

Complex Dose-Response Curves

Nonlinear Regression with Prism

Constraining and Sharing Parameters

Prism’s Nonlinear Regression Dialog

Classic Nonlinear Models Built into Prism

Importing Equations and Equation Libraries

Writing User-Defined Models in Prism

Linear Regression with Prism

Reading Unknowns from Standard Curves

Graphing a Family of Theoretical Curves

Fitting Curves Without Regression