Nate Derby

Nate Derby, Stakana Analytics

Managing and Monitoring Statistical Models
Managing and monitoring statistical models can present formidable challenges when you have multiple models used by a team of analysts over time. How can you efficiently ensure that you’re always getting the best results from your models? In this presentation, we’ll first examine these challenges and how they can affect your results. We’ll then look into solutions to those challenges, including lifecycle management and performance monitoring. Finally, we’ll look into implementing these solutions both with an in-house approach and with SAS® Model Manager.

Using SAS® GTL With 9.3 Updates to Visualize Data When There Is Too Much of It to Visualize
Developing a good graph with ODS statistical graphics becomes a challenge when input data maps to crowded displays with overlapping points or lines. Such is the case with the Framingham Heart Study of 5,209 subjects captured in the sashelp.heart data set, a series of 100 booking curves for the airline industry, and interleaving series plots that capture closing stock values over a 20-year period for three giants in the computer industry. In this presentation, transparency, layering, data point rounding and color coding are evaluated for their effectiveness to add visual clarity to graphics output. SAS version 9.2 compatible Graph Template Language (GTL) plotting statements referenced in the presentation include HISTOGRAM, SCATTERPLOT, BOXPLOT, SERIESPLOT and BANDPLOT plus layouts OVERLAY, GRIDDED, DATAPANEL and LATTICE that produce single or multiple-panel graphs.

GTL 9.3 updates for SAS 9.3 have also been added to the presentation. They include HEATMAPPARM for heat maps that add a third dimension to a graph via color, the DISCRETEOFFSET option that makes it possible to insert output from additional plotting statements into the area between ticks on a discrete axis, the RANGEATTRMAP statement for grouping continuous data in a legend, and DISCRETEATTRMAP for assigning colors to 100 series plot lines. If you have SAS 9.3, you automatically have access to GTL.


Renu Gehring

Renu Gehring, Care Oregon

Tips and Tricks in SQL
The SQL procedure is the jack of all trades and master of several. It combines the functionality of several procedures – Print, Means, Datasets and Contents to name a few. It carries out basic and complex data management tasks with an elegance and compactness able to persuade the most inveterate DATA step enthusiast. As a result, knowledge of PROC SQL is essential for SAS® programming at any level. This presentation contains a multitude of tips and tricks, organized by complexity into three levels: basic, intermediate and advanced. Each tip is accompanied by an explanatory note, relevant code, sample data and visual representation of data.  This format is designed to enable easy comprehension, hands on practice and immediate use of the tips. The hope is that this presentation will galvanize SAS programmers at all levels to tap into the power of PROC SQL.


Britney Gilbert

Britney Gilbert, Juniper Tree Consulting

%MAKE_IT_COUNT: An Example Macro for Dynamic Table Programming
Today there is more pressure on programmers to deliver summary outputs faster without sacrificing quality. By using just a few programming strategies, the %MAKE_IT_COUNT macro is simple, straightforward to understand and easily adapted for changing reporting needs. This presentation shares an example macro and explores the use of MULTILABEL and PRELOADED formats, PROC SUMMARY options and dynamic ARRAYs.

WHERE, Oh, WHERE Art Thou? A Cautionary Tale for Using WHERE Statements and WHERE= Options
Using WHERE statements in your SAS® programming can make processing data more efficient. However, the programmer needs to have a full understanding and be aware of how SAS processes multiple WHERE statements or combinations of WHERE statements and WHERE= dataset options in DATA steps and PROCEDURES. This presentation explores examples of the combinations of WHERE statements and WHERE= dataset options in both DATA steps and PROCEDURES and the resulting logs and output.

Huntley Scott

Scott Huntley, SAS

PDF vs. HTML: Can’t We All Just Get Along
Have you ever asked, “Why doesn’t my PDF output look just like my HTML output?” This paper explains the power and differences of each destination. You’ll learn how each destination works and understand why the output looks the way it does. Learn tips and tricks for how to modify your SAS® code to make each destination look more like the other. The tips span from beginner to advanced in all areas of reporting. Each destination is like a superhero, helping you transform your reports to meet all your needs. Learn how to use each ODS destination to the fullest extent of its powers.

SAS® Style Templates: Always in Fashion
This paper provides an introduction into the use of style templates in SAS 9.2 and forward. Methods of determining the correct style elements will be shown along with several concrete examples of making style template changes. The use of the IMPORT statement will also be demonstrated. In addition to these topics, a job aid will be provided that outlines the most commonly used style elements and their attributes.

Heidi Leverton

Heidi Leverton, Esri Location Analytics

ESRI Maps Framework for SAS®
With Esri Maps Framework, you can add the power of mapping and geospatial analysis to your SAS applications. Choose from a library of widgets to integrate specific mapping functionality into your application, or quickly build mapping into your application using a rich, full-featured application framework.  

The following are just a few examples of what can be done with the mapping and analysis capabilities of Esri Maps Framework:

  • Compose a map with data from multiple sources, including data from ArcGIS.
  • Create dynamic, color-coded, point, clustered-point or heat maps.
  • Add demographics and lifestyle data directly to your business system to get more context about locations that are important to you.
  • Find all locations that are within a certain distance of another location.
  • Share maps with others inside and outside of your organization.


Arthur Li

Arthur Xuejun Li, City of Hope National Medical Center

Essentials of PDV: Directing the Aim to Understanding the DATA Step!
Beginning programmers often tend to focus on learning syntax without understanding how SAS® processes data during the compilation and execution phases. SAS creates a new data set, one observation at a time, from the program data vector (PDV). Understanding how and why each of the automatic or user-defined variables is initialized and retained in the PDV is essential for writing an accurate program. Among these variables, the following variables deserve special attention, including variables that are created in the DATA step, by using the RETAIN or the SUM statement, and via by-group processing (FIRST.VARIABLE and LAST.VARIABLE). In this presentation, you will be exposed to what happens in the PDV and how these variables are retained from various applications.

Shannon Moore

Shannon Moore, SAS

What’s New in SAS® 9.4?
Explore selected changes and enhancements in SAS 9.4, including a discussion of changes to common procedures.

Around the World With PROC GEOCODE
Geocoding is the process of adding geographic coordinates (latitude and longitude values) to an address. After geocoding, the coordinates can be used to display a point on a map or to calculate distances. Geocoding also enables you to add attribute values such as census blocks to an address. This presentation will cover the various geocoding methods, PROC GEOCODE syntax and the associated data sources.

Melodie Rush

Melodie Rush, SAS

Logistic Regression: What Is It and What Can I Learn From It?
This tutorial is designed for someone who does not have a statistical background but may need to predict an outcome using logistic regression. If the words after the “but” in the previous sentence seem like another language, this will be the session designed for you. This tutorial will answer the questions “What is a logistic regression?” and “What will I learn from running a logistic regression on my data?" In the session, simple examples will be used to show how to set up your data, run a logistic regression, and interpret the output.

How to Select the Best Predictor Variables Using SAS® Enterprise Guide® and SAS® Enterprise Miner™
This presentation will answer the what, why and how on variable selection. What is variable selection (sometimes called variable reduction)? Why is it important? And why should it be on your list of activities when doing predictive modeling? How do you perform variable selection using SAS Enterprise Guide and SAS Enterprise Miner? This presentation will include examples for both products.


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