Understanding the gtsummary Package in R: Manipulating Statistics in Tables

Introduction to gtsummary and its Table Functionality

The gtsummary package in R has revolutionized the way we create summary tables for datasets. It provides a user-friendly interface for creating various types of summaries, including mean, median, count, proportion, and more. In this article, we will delve into the world of gtsummary and explore how to manipulate statistics in its table functionality.

Setting Up the Environment

To begin with, make sure you have the gtsummary package installed in your R environment. If not, you can install it using the following command:

install.packages("gtsummary")

Once installed, load the gtsummary package in your R session using the following command:

library(gtsummary)

The Default Statistic Argument

Let’s start by examining the default statistic argument in the tbl_summary() function. According to the documentation, the default value is a list that specifies various types of summary statistics for continuous and categorical variables.

Here’s an example:

iris %>% gtsummary::tbl_summary(
  statistic = list(all_continuous() ~ "{median} ({p25}, {p75})", all_categorical() ~ "{n} ({p}%)")
)

In this code, all_continuous() refers to continuous variables in the dataset (in this case, Sepal.Length, Sepal.Width, etc.), and all_categorical() refers to categorical variables (Species). The summary statistics specified for these variables are median with 25th and 75th percentiles, and count with proportion percentage, respectively.

Error Message Explanation

Now, let’s revisit the error message you encountered:

Error in `statistic=` argument input. Select from ‘Sepal.Length’, ‘Sepal.Width’, ‘Petal.Length’, ‘Petal.Width’, ‘Species’

The error message indicates that the issue lies with the input to the statistic argument. The default value of statistic is not being selected, suggesting that it might be a version-specific or configuration-dependent setting.

Older Versions of R/gtsummary

As mentioned in your edit, the issue was resolved due to an older version of R/gtsummary. This highlights the importance of regularly updating and maintaining packages in our R environment. Ensure you are using the latest stable version of gtsummary.

Troubleshooting Common Issues

To troubleshoot common issues with the statistic argument, follow these steps:

1. Check Package Version: Verify that you are using the latest stable version of gtsummary. You can do this by checking the package’s version using the following command:

library(gtsummary) version(gtsummary)

2.  **Update Package**: If an older version is installed, update to the latest version using the following command:

    ```markdown
update.packages()

3. Check for Conflicting Versions: Ensure there are no conflicting versions of R and gtsummary. You can check for this by running the following commands in R:

R.version$major R.version$minor R.version$patch packageVersion(“gtsummary”)

4.  **Reinstall Package**: If updating does not resolve the issue, try reinstalling `gtsummary` using the following command:

    ```markdown
remove.packages("gtsummary")
install.packages("gtsummary")
library(gtsummary)

Conclusion

Manipulating statistics in tables created with gtsummary can be a straightforward process. However, when encountering errors or unexpected behavior, it is essential to troubleshoot by checking the package version, updating the package, and resolving any potential conflicts.

By following these steps and keeping your R environment up-to-date, you should be able to effectively work with gtsummary and create informative summary tables for your datasets.

Additional Resources

For further learning about gtsummary, we recommend checking out the official documentation and exploring additional tutorials or guides on R-related websites.

Last modified on 2024-01-22