Jason W. Osborne's Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne's applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.
Chapter 11: Modern and Effective Methods of Dealing with Missing Data
Modern and Effective Methods of Dealing with Missing Data
Is emptiness meaningless? Modern researchers seem to view missing data as empty, useless, a void that should have been filled with information, a thing without pattern, meaning, or value. Yet the ancient Greeks saw emptiness as potential, much as a painter sees a blank canvas. The Greek goddess Chaos (Khaos) represented unfilled space (initially the unfilled space between the earth and the heavens in their creation mythology), and ancient Olmec, Indian, and Arabic mathematicians saw usefulness in the mathematical quantification of nothing, what we now call zero (Colebrooke, 1817; Diehl, 2004).
The modern computer era is built upon use of 0s and 1s as indicators of important states, both meaningful and critical to the functioning ...