But it isn't without challenges. Headlines herald new breakthroughs and advances especially in oncology--but the data is actually distorted to skew towards a cure rather than a potential stepping stone.
For example, when I read the statistics sections of clinical research reports I see the interchangeable use of multivariate and multivariable analysis. To begin to see light between these two terms, we need to understand the difference between a categorical and a continuous variable. Here is an excerpt from a small book I wrote as a guide, Improving Numeracy in Medicine.
Multivariate analysis in a sense is referring to statistical models with 2 or more dependent or outcome variables. Multivariable analysis refer to multiple independent or response variables. A simple linear regression model will have a continuous outcome and one predictor while multivariable linear regression models have a continuous outcome and multiple predictors (continuous or categorical).
Whats the big deal? Maybe there isn't one. Remember I am not a statistician but when I see the wrong model being used or described in the methods or results section I begin to arch my eyebrow and try and unpack the mathematics. After all, the articles are written for informed decisions and often--important interpretation at the point of care.