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update Moderation example to best practice and v4 (#297)
* create truncated regression example
* delete truncated regression example from main branch
* create truncated regression example
* delete truncated regression example from main branch
* create truncated regression example
* delete truncated regression example from main branch
* start the update of moderation analysis notebook
* bring back target_accept to resolve divergences
* suggested updates
* add explanation to category
Co-authored-by: Oriol Abril-Pla <[email protected]>
* fix reference: article -> book
* fix a date to match up with references
* attempt to add cross references between moderation and mediation notebooks
* remove pm. tags on mediation notebook while I'm here
* fix notebook cross references
Co-authored-by: Benjamin T. Vincent <[email protected]>
Co-authored-by: Oriol Abril-Pla <[email protected]>
"This notebook covers Bayesian [mediation analysis](https://en.wikipedia.org/wiki/Mediation_(statistics) ). This is useful when we want to explore possible mediating pathways between a predictor and an outcome variable.\n",
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"\n",
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"It is important to note that the approach to mediation analysis has evolved over time. This notebook was heavily influenced by the approach of {cite:t}`hayes2017introduction` as set out in his textbook \"Introduction to Mediation, Moderation and Conditional Process Analysis.\""
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"It is important to note that the approach to mediation analysis has evolved over time. This notebook was heavily influenced by the approach of {cite:t}`hayes2017introduction` as set out in his textbook \"Introduction to Mediation, Moderation and Conditional Process Analysis.\"\n",
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"\n",
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"Readers should be aware that mediation analysis is commonly confused with moderation analysis for which we have a separate example ({ref}`moderation_analysis`)."
Copy file name to clipboardExpand all lines: examples/references.bib
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@@ -9,6 +9,16 @@ @article{ando2007bayesian
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publisher = {Oxford University Press},
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doi = {10.1093/biomet/asm017}
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}
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@article{bauer2005probing,
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title = {Probing interactions in fixed and multilevel regression: Inferential and graphical techniques},
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author = {Bauer, Daniel J and Curran, Patrick J},
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journal = {Multivariate behavioral research},
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volume = {40},
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number = {3},
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pages = {373--400},
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year = {2005},
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publisher = {Taylor \& Francis}
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}
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@book{breen1996regression,
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title = {Regression models: Censored, sample selected, or truncated data},
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author = {Breen, Richard and others},
@@ -117,6 +127,26 @@ @misc{hogg2010data
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archiveprefix = {arXiv},
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primaryclass = {astro-ph.IM}
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}
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@article{iacobucci2016mean,
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title = {Mean centering helps alleviate ``micro'' but not ``macro'' multicollinearity},
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author = {Iacobucci, Dawn and Schneider, Matthew J and Popovich, Deidre L and Bakamitsos, Georgios A},
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journal = {Behavior research methods},
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volume = {48},
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number = {4},
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pages = {1308--1317},
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year = {2016},
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publisher = {Springer}
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}
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@article{iacobucci2017mean,
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title = {Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux},
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author = {Iacobucci, Dawn and Schneider, Matthew J and Popovich, Deidre L and Bakamitsos, Georgios A},
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journal = {Behavior research methods},
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volume = {49},
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number = {1},
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pages = {403--404},
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year = {2017},
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publisher = {Springer}
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}
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@book{ivezić2014astroMLtext,
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author = {\v{Z}eljko Ivezi\'{c} and Andrew J. Connolly and Jacob T. VanderPlas and Alexander Gray},
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doi = {10.1515/9781400848911},
@@ -187,6 +217,12 @@ @article{kruschke2013
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title = {Bayesian estimation supersedes the t test.},
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journal = {Journal of Experimental Psychology: General}
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}
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@book{kruschke2014doing,
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title = {Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan},
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author = {Kruschke, John},
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year = {2014},
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publisher = {Academic Press}
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}
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@misc{kucukelbir2015automatic,
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title = {Automatic Variational Inference in Stan},
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author = {Alp Kucukelbir and Rajesh Ranganath and Andrew Gelman and David M. Blei},
@@ -218,6 +254,16 @@ @book{martin2021bayesian
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publisher = {Chapman and Hall/CRC},
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doi = {10.1201/9781003019169}
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}
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@article{mcclelland2017multicollinearity,
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title = {Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016)},
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author = {McClelland, Gary H and Irwin, Julie R and Disatnik, David and Sivan, Liron},
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journal = {Behavior research methods},
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volume = {49},
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number = {1},
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pages = {394--402},
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year = {2017},
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publisher = {Springer}
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}
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@book{mcelreath2018statistical,
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title = {Statistical rethinking: A Bayesian course with examples in R and Stan},
title = {Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression},
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author = {Spiller, Stephen A and Fitzsimons, Gavan J and Lynch Jr, John G and McClelland, Gary H},
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journal = {Journal of marketing research},
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volume = {50},
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number = {2},
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pages = {277--288},
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year = {2013},
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publisher = {SAGE Publications Sage CA: Los Angeles, CA}
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}
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@misc{szegedy2014going,
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title = {Going Deeper with Convolutions},
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author = {Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
@@ -24,6 +24,8 @@ This notebook covers Bayesian [mediation analysis](https://en.wikipedia.org/wiki
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It is important to note that the approach to mediation analysis has evolved over time. This notebook was heavily influenced by the approach of {cite:t}`hayes2017introduction` as set out in his textbook "Introduction to Mediation, Moderation and Conditional Process Analysis."
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Readers should be aware that mediation analysis is commonly confused with moderation analysis for which we have a separate example ({ref}`moderation_analysis`).
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