Different studies were focused on the determinants of complementary feeding and inadequate MAD among 6–23-month-old children using classical models such as binary and multilevel logistic regression ...

Article citations More>> Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

Understand logistic regression, a key statistical method for relationships with binary outcomes. Explore its formula, assumptions and practical applications.

What exactly is an Anderson-Darling test? Testing for normality is often the first step in analyzing your data. Many ...

Learn More. Logistic regression is a statistical technique used to determine the relationship between two data factors to make a binary prediction.

Key Points Normality refers to how your data fits into a normal distribution. You can find out if your data is uniform by ...

Learning outcomes After successfully completing this course you as a student are expected to be able to: choose a suitable regression model for assessing a specific research hypothesis using data ...

The models used are binary logistic regression models based on the full sample of U.S. adults surveyed for this study. The analyses are based on the weighted sample, thus adjusting for differences in ...