SAS Studio - the next evolution of SAS programming environments
Matt Becker, SAS
SAS Studio is the newest SAS programming environment, and provides many tools to help you with your programming tasks. In this Hands on Training session, we'll take a tour of this enhanced programming environment, highlighting the following features: the dataset browser, where we will build filters and change what columns are displayed, the snippet manager, where we will explore existing code snippets and learn how to create and manage our own code, the task manager, where we will see how to generate code using a GUI, and then see how to build our own tasks, and the visual query builder, where we will see how to combine datasets quickly and efficiently. SAS Studio is a web-based tool, so you will be able to code and interact with SAS from just a browser. Come see how this tool can help you be a more efficient programmer.
Kriss Harris, SAS Specialists Ltd
The workshop will introduce users to GTL and the various layout and show them how create well known requested graphs and also ad hoc graphs. The workshop will also show the advanced features of GTL such as annotation and conditional statements.
The SAS Hash Object: It’s Time To .find() Your Way Around
Peter Eberhardt, Fernwood Consulting Group Inc
The hash object has been introduced a lot in recent year SAS presentations. Most of them were giving examples and explanations on how to apply them. Somehow people may still struggle on the weird syntax. Statements such as if _n_=1, length and call missing etc. are frequently used to support the hash merge and clear the log issue (uninitialized...). This leads to the motivation of encapsulation the hash merge process. Inputting only three parameters: 1. the dataset you want to merge with; 2. the key variables; 3. the new variables you would like to drag into the datasets. That’s all we need to complete a merge without bothering the complex hash syntax.
ggTables: A set of SAS Macros to Automatically Produce Statistical Tables in Clinical Research
Guhong Qiu, Beijing Tiantan Hospital
A Statistical table is one of the most important ways to show statistical results in clinical research. As statistical tables are more concise than text and contain more and exact information than graphs, they are more frequently used in statistical reports or academical articles. SAS has various tools to reduce tables, but neither of them can directly generate statistical tables that meet the requirement of publishing for academical journals. Many SAS users and developers have published their macros that generate statistical tables both with descriptive statistics and P values, however, most of these macros limited to produce only baseline comparison table. As a matter of fact, besides baseline table, there are many other kinds of statistical tables. It’s necessary that we need to summarize these statistical tables and then study how to produce these statistical tables using tools provided by SAS. One macro is not enough, what we need is a set of SAS macros that can produce all kinds of statistical tables for us. The purpose of this paper is to introduce a set of SAS macros that can automatically produce nine kinds of highly customized and ready-to-publish statistical table in RTF format. These user-friendly SAS macros consist of four groups of SAS macros: baselines statistical table macros, outcome statistical table macros, risk factor statistical table macros, and subgroup analysis statistical table macros.