BJ Data Tech Solution

Specialized on Data processing, Data management Implementation plan, Data Collection tools - electronic and paper base, Data cleaning specifications, Data extraction, Data transformation, Data load, Analytical Datasets, and Data analysis. BJ Data Tech Solutions teaches on design and developing Electronic Data Collection Tools using CSPro, and STATA commands for data manipulation. Setting up Data Management systems using modern data technologies such as Relational Databases, C#, PHP and Android.

!= 1 predicts failure perfectly
!= 1 predicts failure perfectly

note: 0b.HX_HTN != 1 predicts failure perfectly
0b.HX_HTN dropped and 14 obs not used
note: 0b.HX_DM != 1 predicts failure perfectly
0b.HX_DM dropped and 5 obs not used

When performing logistic regression, the categorical variable that perfectly predicts failure of binary outcome is dropped, thus reducing the corresponding observation.

Is there any option or setting to conserve observation from dropping?

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!= 1 predicts failure perfectly

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