Main content
Response Surface Analysis: A collection
Date created: | Last Updated:
: DOI | ARK
Creating DOI. Please wait...
Category: Project
Description: This collection of OSF projects brings together several resources for conducting polynomial regression and response surface analyses. On the right side of the screen you find "Components" which are links to subfolders. At the "Files" section you can find more material, such as slides for workshops and talks.
Add important information, links, or images here to describe your project.
Citation
Components
Testing fit patterns with polynomial regression models
Fit hypotheses, also labeled ‘congruence’, ‘discrepancy’, or ‘congruity’ hypotheses, contain the notion that an outcome is optimal when two predictor ...
Concurrent and longitudinal dyadic polynomial regression analyses of Big Five traits and relationship satisfaction: Does similarity matter?
Being with a well-matched partner seems essential for a happy relationship. However, past research on personality similarity in couples has reported i...
Testing similarity effects with dyadic response surface analysis (DRSA)
Simulation code and supplementary material for our paper "Testing similarity effects with dyadic response surface analyses".
The social consequences and mechanisms of personality: How to analyse longitudinal data from individual, dyadic, round-robin and network designs
There is a growing interest among personality psychologists in the processes underlying the social consequences of personality. To adequately tackle t...
Response Surface Analysis in Personality and Social Psychology: Checklist and Clarifications for the Case of Congruence Hypotheses
Response Surface Analysis (RSA) enables researchers to test complex psychological effects, for example, whether the congruence of two psychological co...
Recent Activity
Start managing your projects on the OSF today.
Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.