Nonlinear Regression

REG7

Duration : 0.5 day(s)

:: Course Summary

This workshop offers an overview of nonlinear regression. This special type of regression technique is commonly used to model growth curves and to establish relationships between dose and responses. We discuss the strengths and weaknesses of the techniques, their practical implementation and the interpretation of results produced from the use of these techniques.

:: Learning Objectives

Upon completion of this course, participants will understand the underlying assumptions of the technique and will be able to:

Explain the context of use of nonlinear linear regression

Construct nonlinear regression models

Assess the goodness-of-fit of the model to the data

Identify common issues in nonlinear regression, diagnose problems and fix them

Interpret statistical software output

:: Target Audience

This applied training session in statistics is aimed at all who collect data and who must make decisions based on that data. The regression techniques covered in this session will be particularly useful for people who are interested in relating/predicting a variable to/from a single or a set of explanatory variables when the relationship between variables is not strictly linear.

:: Prerequisite

This half-day training session covers nonlinear regression, a statistical technique used to study the relationship between a continuous dependent variable and a set of explanatory or independent variables.

Participants should know the essential tools in statistics - descriptive statistics, both numerical (mean, standard deviation, standard error, etc.) and graphical (histogram, box-plot, scatter plot, etc.), and hypothesis testing and confidence intervals.

Potential participants should either have attended the training session Fundamental Tools in Statistics or should possess a similar background.

Potential participants should either have attended the training session Linear and Multiple Linear Regression Techniques or by possessing a similar background.

:: Topics Covered

What is a Nonlinear Model?
- Linearizable models
- True nonlinear models
Mechanism of Nonlinear Regression
- Algorithm
- Estimation of model coefficients
- Interpretation of model coefficients
Specific Issues in Nonlinear Regression
- Selection of starting values
- Fixing the value of certain parameters
- Calculating an Rsquare-type measure
- Choosing the fitting algorithm
- Calculating predicted values and their confidence intervals
Goodness-of-Fit Measures
Applications
- Growth curves
- Pharmacokinetics
- Modeling dose-response

:: Course Content

This half-day session covers nonlinear regression which is a technique used to quantify the relationship between variables when it is not strictly linear.
The training covers the objectives of nonlinear regression analysis, the principle of modeling, parameter estimation, as well as interpretation of model coefficients, goodness-of-fit and validation measures, and prediction in regression. We place special emphasis on problems commonly encountered in regression, ways to detect these problems and ways to solve them.