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Classification Crosswalks: Strategies in Data Transformation

What if you have too many categories in a categorical variable? Your cardinality is too high for a chi-square analysis.

Classification crosswalks are easy to make, and can help you reduce cardinality in categorical variables, making for insightful data science portfolio projects with only descriptive statistics. Read my blog post for guidance!

R for Logistic Regression: Example from Epidemiology and Biostatistics

Logistic regression calculate the log odds of the probability of the outcome. Many people are used to using SAS for logistic regression, but you can also use R.

R for logistic regression in health data analytics is a reasonable choice, if you know what packages to use. You don’t have to use SAS! My blog post provides you example R code and a tutorial!

The Paste Command in R is Great for Labels on Plots and Reports

The paste command is used to concatenate strings in R. You can use it different ways, which is what I demonstrate in my blog and videos.

The paste command in R is used to concatenate strings. You can leverage the paste command to make refreshable label objects for reports and plots, as I describe in my blog post.

Adding Error Bars to ggplot2 Plots Can be Made Easy Through Dataframe Structure

Error bars on plots can provide the audience an estimate of the amount of certainty you have with your estimates.

Adding error bars to ggplot2 in R plots is easiest if you include the width of the error bar as a variable in your plot data. Read my blog post to see an example.

Data Curation Solution to Confusing Options in R Package UpSetR

It is possible to use data curation to solve the problem of a confusion vector containing options.

Data curation solution that I posted recently with my blog post showing how to do upset plots in R using the UpSetR package was itself kind of a masterpiece. Therefore, I thought I’d dedicate this blog post to explaining how and why I did it.

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