Publications by Steven P. Sanderson II, MPH
ADF and Phillips-Perron Tests for Stationarity using lists
Introduction A time series is a set of data points collected at regular intervals of time. Sometimes, the data points in a time series change over time in a predictable way. This is called a stationary time series. Other times, the data points change in an unpredictable way. This is called a non-stationary time series. Imagine you are playing a g...
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Another Post on Lists
Introduction Manipulating lists in R is a powerful tool for organizing and analyzing data. Here are a few common ways to manipulate lists: Indexing: Lists can be indexed using square brackets “[ ]” and numeric indices. For example, to access the first element of a list called “mylist”, you would use the expression “mylist[1]”. Subset...
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Simplifying List Filtering in R with purrr’s keep()
Introduction The {purrr} package in R is a powerful tool for working with lists and other data structures. One particularly useful function in the package is keep(), which allows you to filter a list by keeping only the elements that meet certain conditions. The keep() function takes two arguments: the list to filter, and a function that returns ...
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Service Line Grouping with {healthyR}
Introduction Healthcare data analysis can be a complex and time-consuming task, but it doesn’t have to be. Meet {healthyR}, your new go-to R package for all things healthcare data analysis. With {healthyR}, you can easily and efficiently analyze your healthcare data, and make sense of the information it contains. One of the key features of {hea...
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Transforming Your Data: A Guide to Popular Methods and How to Implement Them with {healthyR.ai}
Introduction Transforming data refers to the process of changing the scale or distribution of a variable in order to make it more suitable for analysis. There are many different methods for transforming data, and each has its own specific use case. Box-Cox: This is a method for transforming data that is positively skewed (i.e., has a long tail t...
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