Editing Logistic regression (section)

====Pseudo-R-squared====
{{main article| Pseudo-R-squared}}
In linear regression the squared multiple correlation, {{mvar|R}}<sup>2</sup> is used to assess goodness of fit as it represents the proportion of variance in the criterion that is explained by the predictors.<ref name=Cohen/> In logistic regression analysis, there is no agreed upon analogous measure, but there are several competing measures each with limitations.<ref name=Cohen/><ref name=":0">{{cite web |url=https://support.sas.com/resources/papers/proceedings14/1485-2014.pdf |title=Measures of fit for logistic regression |last=Allison |first=Paul D. |publisher=Statistical Horizons LLC and the University of Pennsylvania}}</ref>

Four of the most commonly used indices and one less commonly used one are examined on this page:
* Likelihood ratio {{mvar|R}}<sup>2</sup>{{sub|L}}
* Cox and Snell {{mvar|R}}<sup>2</sup>{{sub|CS}}
* Nagelkerke {{mvar|R}}<sup>2</sup>{{sub|N}}
* McFadden {{mvar|R}}<sup>2</sup>{{sub|McF}}
* Tjur {{mvar|R}}<sup>2</sup>{{sub|T}}