Case are designated as typical (= well predicted) and deviant (= badly predicted) based on the prediction interval. The x% prediction interval represents the range that we expect to include x% of outcome values in repeated samples. For example, a 95% prediction interval ranging from 0-5 conveys that 95% of future outcome values will be in the range of 0-5. If the observed outcome is inside the prediction interval, the case is classified (or designated) as typical and as deviant otherwise.
predint(lmobject, piwidth = 0.95)
Object generated with
Width of the prediction interval (default is 0.95).
Proposed by Rohlfing, Ingo and Peter Starke (2013): Building on Solid Ground: Robust Case Selection in Multi-Method Research. *Swiss Political Science Review* 19 (4): 492-512. (https://doi.org/10.1111/spsr.12052)
A dataframe with the observed outcome, fitted outcome, upper and lower bound of the % prediction interval and classification of cases as typical or deviant.
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