Why logistic regression for public health rather than just logistic regression? Well, there are some particular considerations for every data set, and public health data sets have particular features that need special attention. In a word, they're messy. Like the others in the series, this is a hands-on course, giving you plenty of practice with R on real-life, messy data, with predicting who has diabetes from a set of patient characteristics as the worked example for this course. Additionally, the interpretation of the outputs from the regression model can differ depending on the perspective that you take, and public health doesn’t just take the perspective of an individual patient but must also consider the population angle. That said, much of what is covered in this course is true for logistic regression when applied to any data set, so you will be able to apply the principles of this course to logistic regression more broadly too.Lee mas.
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Las técnicas y herramientas cubiertas en Logistic Regression in R for Public Health son muy similares a los requisitos que se encuentran en los anuncios de trabajo de Científico de datos.
Logistic Regression in R for Public Health is a part of uno structured learning path.
4 Courses
4 Months
Statistical Analysis with R for Public Health
