The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs![Blog posts from 2023 that deserve a second look](https://blogs.sas.com/content/iml/files/2023/09/sganno5-640x336.png)
In a previous article, I presented some of the most popular blog posts from 2023. The popular articles tend to discuss elementary topics that have broad appeal. However, I also wrote many technical articles about advanced topics. The following articles didn't make the Top 10 list, but they deserve a
![Reporting statistics for unobserved levels of categorical variables](https://blogs.sas.com/content/iml/files/2023/12/classdata4.png)
An unobserved category is one that does not appear in a sample of data. For example, in a small sample of US voters, you are likely to observe members of the major political parties, but less likely to observe members of minor or fringe parties. This can cause a headache
![Top 10 posts from The DO Loop in 2023](https://blogs.sas.com/content/iml/files/2023/05/Simpson4-640x336.png)
In 2023, I wrote 90 articles for The DO Loop blog. My most popular articles were about SAS programming, data visualization, and statistics. In addition, several "general interest" articles were popular, including my article for Pi Day and an article about AI chatbots. If you missed any of these articles,
![The difference between frequencies and weights in a correlation analysis](https://blogs.sas.com/content/iml/files/2023/12/weightedCorr4-400x336.png)
Statistical software often includes supports for a weight variable. Many SAS procedures make a distinction between integer frequencies and more general "importance weights." Frequencies are supported by using the FREQ statement in SAS procedures; general weights are supported by using the WEIGHT statement. An exception is PROC FREQ, which contains
![Estimate polychoric correlation by maximum likelihood estimation](https://blogs.sas.com/content/iml/files/2023/12/polychor5-480x336.png)
SAS provides many built-in routines for data analysis. A previous article discusses polychoric correlation, which is a measure of association between two ordinal variables. In SAS, you can use PROC FREQ or PROC CORR to estimate the polychoric correlation, its standard error, and confidence intervals. Although SAS provides a built-in
![What is polychoric correlation?](https://blogs.sas.com/content/iml/files/2023/12/polychor3-480x336.png)
Correlation is a statistic that measures the association between two variables. When two variables are positively correlated, low values of one variable tend to be associated with low values of the other variable. Medium values and high values are similarly associated. For negative correlation, the association is flipped: low values