A Mathematical Tool for Inference in Logistic Regression with Small-Sized Data Sets: A Practical Application on ISW-Ridge Relationships

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td align="left">Criterion</td><td align="center"> DF</td><td align="center">Value</td><td align="center">Value/DF</td><td align="center">Pr  &gt;  Chi-sq</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td align="left">
										Deviance </td><td align="center">49</td><td align="center">16.5436</td><td align="center"> 0.3376</td><td align="center">1.0000</td></tr><tr><td align="left">Pearson</td><td align="center">49</td><td align="center">23.2826</td><td align="center"> 0.4752</td><td align="center">0.9993</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

 Deviance and Pearson goodness-of-fit statistics.

Mathematical Problems in Engineering

tab2

Table 2

Table 2: A Mathematical Tool for Inference in Logistic Regression with Small-Sized Data Sets: A Practical Application on ISW-Ridge Relationships 