In many regression problems, data on the dependent variable are censored; that is, the values of some observations are known only to be above or else below some value. Such data often arise in ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Logistic Regression Using the SAS System: Theory and Application is for ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

ABSTRACT In this paper, we investigate the linearity versus nonlinearity of the Large Magellanic Cloud (LMC) Cepheid period‐luminosity (P‐L) relation using two statistical approaches not previously ...