Linear Regression by Martin Peter;

Author:Martin, Peter; [Martin, Peter]
Language: eng
Format: epub
Publisher: SAGE Publications
Published: 2021-11-09T10:28:18.033967+00:00

Multivariate relationships: a simple example with two predictors

Confounding and suppression are important concepts and can be a motivation for multivariate analysis. On the other hand, often in social science we might not have a clear causal theory that would allow us to decide, for example, which of two predictors of an outcome is a cause, and which a confounder. Sometimes we might more simply be interested in investigating how two (or more) variables act together in their relationships with an outcome. This section introduces a simple research example that helps us think about different types of multivariate relationships we might find in practice.

Consider what determines how happy people are in their lives, how well they feel mentally. Is it money? Status? Success? Physical health? Romantic love? Relationships with friends and family? Being part of a community? Studies into mental wellbeing have investigated many contributing factors, and of course these factors don’t need to be mutually exclusive. Let’s begin by focusing on just two potential predictors of mental wellbeing:

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