In this week’s Brief, we look at hierarchical and mixed models. Our course spotlight is April 10 – May 8: Generalized Linear Models April 24 – May 22: Mixed and Hierarchical Linear Models See you in class! – Peter Bruce Founder, Author, and Senior Scientist Mixed Model – When to Use? In 1861, the BritishContinue reading “Mar 2: Statistics in Practice”
Daily Archives: March 3, 2020
Problem of the Week: Notify or Don’t Notify?
Our problem of the week is an ethical dilemma, posed by the New England Journal of Medicine to its readers 10 days ago. Volunteers contributed DNA samples to investigators building a genetic database for study, on condition the data would be deidentified and kept confidential and that they themselves would not learn results. Should participantsContinue reading “Problem of the Week: Notify or Don’t Notify?”
Factor
The term “factor” has different meanings in statistics that can be confusing because they conflict. In statistical programming languages like R, factor acts as an adjective, used synonymously with categorical – a factor variable is the same thing as a categorical variable. These factor variables have levels, which are the same thing as categories (aContinue reading “Factor”
Mixed Models – When to Use
Companies now have a lot of data on their customers at an individual level. Suppose you are tasked with forecasting customer spending at a grocery chain, and you want to understand how customer attributes, local economic factors, and store issues affect customer spending. You could design your study with hierarchical and mixed linear modeling methodsContinue reading “Mixed Models – When to Use”