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Parsimony is absolutely essential and pervasive. Second and more practically, parsimonious models of scientific data can facilitate insight, improve accuracy, and increase efficiency. Remarkably, parsimonious models can be more accurate than their data.
23 Σεπ 2020 · A parsimonious model is a model that achieves a desired level of goodness of fit using as few explanatory variables as possible. The reasoning for this type of model stems from the idea of Occam’s Razor (sometimes called the “Principle of Parsimony”) which says that the simplest explanation is most likely the right one.
The principle of parsimony reflects the notion that researchers should strive for simple measurement models that use the minimum number of parameters needed to explain a given phenomenon (Raykov & Marcoulides, 1999).
Parsimony in the sense of Popper’s theoretical simplicity requirement is an accepted criterion for judging empirical scientific research. But it is only one of a set of such criteria.
Current approaches fall short in considering the principle of parsimony (Occam ’s Razor), often equating it with the number of model parameters. Here we offer a toolkit for researchers to bet- ter study and understand parsimony through the fit propensity of structural equation models.
1 Ιαν 2022 · Parsimony is the well-established basic principle in the study of animal behavior, and in science, this principle is applied as discovery tool that guides researcher for the development of scientific models (Epstein 1984).
stand the concept of parsimony, particularly its role in testing a hypothesis about an incompletely specified model to establish its objective validity. More parsimonious models represent more complete hypotheses having more ways of being tested and possibly being discontinued. Mulaik also shows that even within the context of the
