Moderation in Management Research: What, Why, When, and How. Dawson, J. F. Journal of Business and Psychology, 29(1):1–19, March, 2014.
Moderation in Management Research: What, Why, When, and How [link]Paper  doi  abstract   bibtex   
Many theories in management, psychology, and other disciplines rely on moderating variables: those which affect the strength or nature of the relationship between two other variables. Despite the near-ubiquitous nature of such effects, the methods for testing and interpreting them are not always well understood. This article introduces the concept of moderation and describes how moderator effects are tested and interpreted for a series of model types, beginning with straightforward two-way interactions with Normal outcomes, moving to three-way and curvilinear interactions, and then to models with nonNormal outcomes including binary logistic regression and Poisson regression. In particular, methods of interpreting and probing these latter model types, such as simple slope analysis and slope difference tests, are described. It then gives answers to twelve frequently asked questions about testing and interpreting moderator effects.
@article{dawson_moderation_2014,
	title = {Moderation in {Management} {Research}: {What}, {Why}, {When}, and {How}},
	volume = {29},
	issn = {0889-3268, 1573-353X},
	shorttitle = {Moderation in {Management} {Research}},
	url = {http://link.springer.com/10.1007/s10869-013-9308-7},
	doi = {10.1007/s10869-013-9308-7},
	abstract = {Many theories in management, psychology, and other disciplines rely on moderating variables: those which affect the strength or nature of the relationship between two other variables. Despite the near-ubiquitous nature of such effects, the methods for testing and interpreting them are not always well understood. This article introduces the concept of moderation and describes how moderator effects are tested and interpreted for a series of model types, beginning with straightforward two-way interactions with Normal outcomes, moving to three-way and curvilinear interactions, and then to models with nonNormal outcomes including binary logistic regression and Poisson regression. In particular, methods of interpreting and probing these latter model types, such as simple slope analysis and slope difference tests, are described. It then gives answers to twelve frequently asked questions about testing and interpreting moderator effects.},
	language = {en},
	number = {1},
	urldate = {2018-10-09TZ},
	journal = {Journal of Business and Psychology},
	author = {Dawson, Jeremy F.},
	month = mar,
	year = {2014},
	pages = {1--19}
}
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