17: Model Specification and Biological Hypotheses

Author

Affiliation

Smit, A. J.

University of the Western Cape

1 Introduction

This chapter addresses the critical first step in statistical modeling: translating a biological hypothesis into a formal mathematical model. We will explore how to select variables that accurately represent ecological processes and define the model structure to correctly test our ideas. This step is foundational, coming after understanding potential pitfalls like collinearity and before more advanced topics in model comparison and interpretation.

2 Key Concepts

• Matching Predictors to Biological Processes: Ensuring that the variables included in the model have a plausible, theoretically-grounded link to the response variable.
• Omitted Variable Bias: Understanding how leaving out a relevant predictor can bias the coefficients of the variables that are included in the model.
• Functional Form: Deciding whether the relationship between predictors and the response is linear or if a nonlinear form (e.g., polynomial, logarithmic) is more appropriate.
• Interactions (Conceptual Introduction): Introducing the idea that the effect of one predictor may depend on the level of another.

This chapter is a placeholder. Content will be developed further.