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In this regard a new explanatory term called Structure Failure Rate (SFR) is introduced.
For instance, correlation is a descriptive term with empirical relevance, while causation is an explanatory term associated with theoretical attempts to understand correlations.
The contribution of each explanatory term was tested sequentially, with non-significant terms removed from the model to produce the minimal model following standard stepwise deletion [43].
As rurality was the only statistically significant variable, the final model only included this explanatory term.
Network distance to the nearest supermarket was added as an explanatory term.
The overall significance of the explanatory term was determined through model comparison using likelihood ratio tests [ 55].
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Here, adjusted R2 is presented, which is a modification of R2 that adjusts for the number of explanatory terms in a model.
While the notion of grounding is often introduced in explicitly explanatory terms, there are two importantly different ways of maintaining that there is a tight connection between grounding and explanation.
Quantitative baseline characteristics were compared using an analysis of variance model with similar explanatory terms.
The significance (two-tailed) of the explanatory terms was determined using the Wald statistic, which approximates the χ distribution.
Wald χ statistics (Bolker et al., 2009) and p values were obtained from models containing all explanatory terms.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com