Matlab scripts for Model I and Model II regressions

A basic introduction to Model I and Model II linear regressions:

• what they are,
• how they are different,
• why they are different,
• and when to use them.

A brief history of Model II regressions.

• Who led the intellectual development of these regression techniques.
• Plus, a list of their seminal papers.

An index of downloadable files for use with MATLAB®.

• Model I regressions: normal (Y-on-X), reversed (X-on-Y) and weighted (wY-on-X).
• Model II regressions: major axis, geometric mean and least-squares-cubic.
• Summary of modifications made to these files.

Some rules of thumb to help decide which model regression to use:

• When to use Model I vs Model II.
• Within each type, which of the various models to use.

Testing Model I and Model II regressions:

• Evaluate the Model I linear regressions using data from Bevington and Robinson (2003)
• Examine the results for standard and weighted regressions.
• Download the data files – Table 6.1 and Table 6.2ASCII text file format
• Compare both linear regression models.
• Download the data file. ASCII text file format
• Examine the results from the various regression models.
• View graphs of the regression models.
• How to know which regression you are using.

For further reading regarding Model I and II regressions, see:

• Ricker (1973). Linear regressions in Fishery Research. J. Fish. Res. Board Can. 30: 409-434.
• Laws and Archie (1981). Appropriate use of regression analysis in marine biology. Marine Biology 65: 13-16.
• Bevington & Robinson (1992). Data Reduction and Error Analysis for the Physical Sciences, Second Edition, McGraw-Hill, Inc., New York.
• Sokal and Rohlf (1995). Biometry, 3rd edition. W.H. Freeman and Company, San Francisco, CA.
• Laws (1997). Mathematical Methods for Oceanographers. John Wiley and Sons, Inc., New York, NY.
• Bevington & Robinson (2003). Data Reduction and Error Analysis for the Physical Sciences, Third Edition, McGraw-Hill, Inc., New York.

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