This post shows a variety of techniques including how to use PROC TEMPLATE and the SOURCE statement, PROC SGPLOT with multiple Y-axis tables, create comparable axes in two side-by-side graphs, create a broken axis, write and use a table template that wraps text, and find and display examples of certain statements in graph templates and fonts in style templates.
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SG annotation is a powerful technique for adding text, lines, arrows, shapes, and images to graphs. This post provides a macro that can help you when you make a mistake in writing the annotations.
One key aspect of graphs used in the statistical or clinical research domains is the need to display numerical or textual information aligned with the data in the plot. Examples of such graphs are the Survival Plot or the Forest Plot. These graphs use the AXISTABLE statements available with SAS
As many of the regular readers of this blog know, SGPLOT and GTL, provide extensive tools to build complex graphs by layering plot statements together. These plots work with axes, legends and attribute maps to create graphs that can scale easily to different data. There are, however, many instances where
Today's post illustrates the REG, PBSPLINE, LOESS, SERIES, and SPLINE statements in PROC SGPLOT. The GROUP= and BREAK options in the SERIES statement are also discussed.
The advent of the AXISTABLE statement with SAS 9.4, has made it considerably easier to create graphs that include statistics aligned with x-axis values (Survival Plot) or with the y-axis (Forest Plot). This statement was specifically designed to address such needs, and includes the options needed to control the text attributes of
A Volcano Plot is a type of scatter-plot that is used to quickly identify changes in large data sets composed of replicate data. In the clinical domain, a Volcano Plot is used to view Risk difference (RD) of AE occurrence (%) between drug and control by preferred term. One example of
Early last year I wrote an article on how to create the "Most Frequent Adverse Events Sorted by Relative Risk" graph using the SGPLOT procedure. The key issue here is that such a graph normally displays two plots side by side, a scatter plot of the proportion values by treatment
When we first released GTL and SG Procedures back with SAS 9.2, Box Plots and Bar Charts would always treat the category axis as discrete. We realized soon enough that we need to support box plots on scaled interval axes for many clinical applications, and this was added in SAS
We all want to customize our graphs just so, and have our personal preferences. Over the past few releases SG Procedures and GTL have added options to customize the look and feel of our graphs. In this article, I will describe new ways in which you can customize your legends. We will also see some