The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs![How to align the Y and Y2 axes in PROC SGPLOT](https://blogs.sas.com/content/iml/files/2019/01/Yaxes6-640x336.png)
When you overlay two series in PROC SGPLOT, you can either plot both series on the same axis or you can assign one series to the main axis (Y) and another to a secondary axis (Y2). If you use the Y and Y2 axes, they are scaled independently by default,
![10 posts from 2018 that deserve a second look Process flow diagram shows how to resample data to create a bootstrap distribution.](https://blogs.sas.com/content/iml/files/2018/12/bootstrapSummary-702x336.png)
Numbers don't lie, but sometimes they don't reveal the full story. Last week I wrote about the most popular articles from The DO Loop in 2018. The popular articles are inevitably about elementary topics in SAS programming or statistics because those topics have broad appeal. However, I also write about
![Deming regression for comparing different measurement methods](https://blogs.sas.com/content/iml/files/2018/12/DemingReg1-640x336.png)
Deming regression (also called errors-in-variables regression) is a total regression method that fits a regression line when the measurements of both the explanatory variable (X) and the response variable (Y) are assumed to be subject to normally distributed errors. Recall that in ordinary least squares regression, the explanatory variable (X)
![Top posts from The DO Loop in 2018 Calibration plot for a misspecified logistic model](https://blogs.sas.com/content/iml/files/2018/05/calibrationplot2-640x336.png)
Last year, I wrote more than 100 posts for The DO Loop blog. Of these, the most popular articles were about data visualization, SAS programming tips, and statistical data analysis. Here are the most popular articles from 2018 in each category. Data Visualization Visualize repetition in song lyrics: In one
![Visualize a mixed model that has repeated measures or random coefficients](https://blogs.sas.com/content/iml/files/2018/12/VizMixed3-640x336.png)
I regularly see questions on a SAS discussion forum about how to visualize the predicted values for a mixed model that has at least one continuous variable, a categorical variable, and possibly an interaction term. SAS procedures such as GLM, GENMOD, and LOGISTIC can automatically produce plots of the predicted
![Create a probability plot in SAS](https://blogs.sas.com/content/iml/files/2018/12/ProbPlot4-640x336.png)
Many data analysts use a quantile-quantile plot (Q-Q plot) to graphically assess whether data can be modeled by a probability distribution such as the normal, lognormal, or gamma distribution. You can use the QQPLOT statement in PROC UNIVARIATE to create a Q-Q plot for about a dozen common distributions. However,