How to Add Parentheses and Significance Stars to Your Estimates Table in R

Описание: Learn how to format your estimates and standard errors table in R by adding parentheses for standard errors and significance stars based on p-values.
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Transforming Your Estimates Table in R

When analyzing data in R, you often need to present your statistical results clearly and concisely. One common task is transforming a table of estimates and standard errors into a more readable format. Specifically, you may want to:

Surround standard errors with parentheses.

List standard errors as rows beneath their corresponding estimates.

Add asterisks to denote significance levels based on p-values.

In this guide, we will guide you through the process of formatting your data frame to make the most out of your estimates table using dplyr, glue, and kableExtra.

Understanding the Data Structure

Before diving into the solution, let’s first look at an example data frame that we will be working with. Your data frame currently consists of models, estimates (e1, e2, e3), and standard errors (sd1, sd2, sd3). Here’s a look at the data:

[[See Video to Reveal this Text or Code Snippet]]

Step-by-Step Solution

1. Calculate p-Values

First, you need to compute the z-scores and p-values for your estimates:

[[See Video to Reveal this Text or Code Snippet]]

2. Define a Function for Significance Stars

Next, create a function p_text that converts p-values into significance stars:

[[See Video to Reveal this Text or Code Snippet]]

3. Transform the Data Frame

Transform the estimates by incorporating standard errors in parentheses and appending significance stars. Use the glue package for easier string interpolation:

[[See Video to Reveal this Text or Code Snippet]]

4. Create the Kable Table

Finally, format the table output using kable and kableExtra for a polished look:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By following the steps outlined above, you will successfully transform your estimates table into a more reader-friendly format. Not only will the standard errors be displayed in parentheses below their estimates, but you'll also provide visual cues regarding their significance, making your results easier to interpret.

This approach is particularly useful when sharing results in reports or publications, ensuring clarity and professionalism in your data presentation.

Happy coding with R!