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SAS healthcare workshop 18 nov 2011

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SAS Healthcare workshop shares some of the best practises in the use of business analytics in the healthcare industry

SAS Healthcare workshop shares some of the best practises in the use of business analytics in the healthcare industry

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  • Understand the process of migration across versions.  We want to know the detailed process of migrating campaigns created in the current version to 5.4.1 Testing:  Performance benchmarks in SAS Test environments of the new version Testing: Do you have any performance test cases that can be shared with us? Integration with Enterprise Miner: How can we use the models built in EM in CI Studio for ( ex) campaign exclusions? InfoMap design best practices and Change Management:Please provide case studies/ examples on how InfoMap strategy has been built in large multi-market environments such as ours. We understand overall concept, we would like to see some details from actual implementationsDoes the upward limit of 1000-1500 variables in the InfoMap remain in the new version or is there any improvement?Explain process around integrating “ local data” ( we have used SAS data sets in PH), governance aspects around UDFs, any other constraintsUse the data from these external data sources in the export file- other than doing some post processing(using process node or Enterprise guide), is there any other way in the next version? Requirement is to integrate some fields from the external sources with some fields in the InfoMap to create the export definitionIn Citi in EDW Rainbow releases, product entities are added incrementally. For ex, Cards and Client module are implemented first, followed by Bank , then Channels and so on. What is the impact of such an incremental build in the InfoMap –(for ex contact history is at the account level which is Phase 2). What is the impact of change on InfoMap ( especially Contact History) due to changing table and data item on which Subject ID is maintained? This will happen across all markets as the Go-to approach is a phased approach hence important to understand this.PROCINFOMAP:  Automation in creating InfoMap. As of now, we are creating InfoMap using the Studio. In big implementations is it advisable to use “procinfomap “  to generate infomap with excel sheet as source for infomap metadata. Can complete infomap be built with procinfomap in newer version Frequency of Contact ManagementBest practices for large implementations, with large data volumesManual testing process when two or more ad hoc campaigns are selected  Calculated variablesHow is large transaction data handled when the selection criteria is always dynamic ? Ex: Transaction code, Merchant description that uses a “ Like” operator, Date that can range from say 15 days to 3 months or so, average spends and not absolute spends using the same criteria as above is requiredNote that because of the dynamic nature of the selection criteria, we cannot have these fields in the databasePerformance issues on calculated variables: Current analysis shows that this is due to limited Oracle functions being supported and the date variables.  We do not know if there is any other issue here. Would like a confirmation and some performance benchmarking that we will not have the same issues in the next version as both the above reasons are said to be resolved?
  • Outline of the workshop
  • SAS was the first, and after 35 years remains the foremost, provider of advanced analytics software. What makes SAS the leader? Above all, it’s providing The Power to Know®. But let’s go into a little more detail on exactlyWHAT SAS helps you to doWHY you would choose SAS as a partnerAnd HOW exactly do we use our software to do what we doTalking Points (scroll down) Addressing new challenges requires a new way of looking at your business. And that’s what the SAS Business Analytics Framework is all about. Traditional decision-making techniques have not yielded optimal results, leaving blind spots that are filled by a gut-level approach. Ad hoc decision making is devoid of true discovery. This makes it impossible to implement transformational approaches that can drive organizations forward. Through the combined strengths without (WITHIN??) the SAS Business Analytics Framework, SAS facilitates every aspect of fact-based, proactive decision making. With our Business Analytics Framework, you can choose the solutions and capabilities you need right now, and achieve results in months not years. Then you can add new functionality over time…all from one vendor, all through one framework. Let’s dive a bit deeper…
  • Through the combined strengths of our business solutions and technologies, SAS provides ultimate flexibility in how organizations deploy analytics to solve business problems.  In its SWOT analysis of SAS, Gartner comments: “SAS took a solution-oriented route more than a decade ago, which now gives the company the advantage of having the widest variety of cross-functional and vertically specific analytic applications out of the box. SAS is the market share leader, and no other vendor in the analytics space can match SAS’ breadth today. This enables (SAS) to go to its customers with a content and solution-driven story instead of offering only technical capabilities.” Reflecting SAS’ rich industry domain expertise, SAS industry solutions surface information in the context of each industry’s unique business processes.Examples include credit risk management in Financial Services, expediting drugs to market in Life Sciences, identifying cross-sell opportunities in Retail, and demand-driven forecasting in Manufacturing. SAS also provides cross-functional solutions that address challenges facing every organization, regardless of industry. Examples include increasing the value of customer relationships…measuring and managing risk…detecting and preventing fraud…maximizing output while controlling costs…optimizing IT networks…and aligning strategy, finance and the workforce for improved outcomes.  When a company chooses SAS, the foundation we provide for solving problems is based on three key capabilities:
  • The ability to manage data is becoming more problematic due to increasing data volumes, velocity, frequency and complexity. This has been exacerbated by the massive growth of unstructured documents such as e-mails, text documents, presentations, images, video files, etc.SAS helps our customers manage and govern this data deluge (both structured and unstructured) by providing a unified approach that includes data integration, data quality, data mastering and enterprise data access.SAS data management is tightly integrated with the analytics capability that is at the heart of SAS business solutions. This integration ensures accuracy and faster time to value.SAS provides the highest level of reliability, availability and performance in demanding real-time environments—from highly optimized data access to high-performance computing options that include grid technology.  Add/substitute proof points specific to your audience or country
  • Analytics ….underpins The Power to KnowSAS is the world leader in advanced analytics that fuel evidence-based answers—enabling organizations to measure what matters today, reveal best actions, expose threats, and incorporate learning into business processes.By collecting, exploring, analyzing and interpreting data to surface patterns, anomalies, key variables and relationships, SAS analytics unveil predictive insights that can be easily shared to compel the right actions throughout the organization. With SAS’ unique depth and breadth of analytics—including statistics, data mining, text analytics, forecasting, econometrics, operations research, quality improvement, and model management—users can learn over time by testing alternatives, building models and measuring results that enable continuous innovation and improvement.Real-time decision management solutions—combining SAS analytics with business logic and contact strategies—help organizations boost profitability with automated decision processes…and meet customer’s needs at the right time and place—in the right context.No one advances the art of analytics better than SAS—through a robust analytics training curriculum, collaborative programs with our key business partners and leading industry experts, ongoing Web seminars, and a wide range of SAS Analytical Service offerings.  Add/substitute proof points specific to your audience or country
  • Enabling fact-based decision making requires getting the right information to the right people at the right time. SAS provides a suite of intuitive interfaces that allow everyone—at every skill level—to access and produce reports with speed and agility.SAS real-time analytics can now be deployed directly to mobile devices, allowing every decision maker—everywhere—to monitor key metrics and make informed decisions. With SAS, reporting is not a stand-alone activity but rather a part of a seamless approach for creating and sharing intelligence. By integrating data management, analytics and reporting as part of one process, SAS makes it easy to get answers to more sophisticated questions, format presentation-quality results, and easily share findings to empower operational decision making.  Add/substitute proof points specific to your audience or country
  • Would this be more a DI issue. How is it related to EG?It is, but the big thing now ongoing in healthcare is integrating all databases to achieve the single patient view. In this context, this and the next one are good examples.
  • Again it seems a DI problemAgain this is in context with the ongoing situation in Singapore.
  • SAS EG is the perfect tool for Statistics, Analytics and Reporting as it offers the ideal environment to carry out simple and complex task. It’s a comprehensive tool that can offer a little bit of DI, access to Statistics and Analytics as well as reporting. You can import data from different sources, join it together, manipulate it, analyze it with statistical techniques and produce some reporting in html, pdf, word and more.
  • Product overview and introductionBusiness analysts, programmers and statisticians can leverage the power of SAS transparently on many platforms. They can access data quickly, manipulate it, perform basic reporting and carry out basic and complex analyses. With SAS Enterprise Guide, they can also distribute the results to targeted groups of users, disseminating the latest intelligence to those who need it for making decisions quickly and effectively. If I had to pick three things I’d say Easy to use, Intuitive and Quick
  • But what can EG do?Graphical user interface • Intuitive wizards provide access to SAS capabilities from basic reporting to complex analyses. • Each wizard has a wide range of flexible options that are easily adjusted. • The graphical query builder enables you to subset data, a log is generated with information about processing, including notes, warnings and errors. • Results can be delivered in HTML, RTF, PDF, SAS report and text formats. Most results also can be output as SAS data sets for further analysis with other tasks. SAS report formats can be shared with SAS Web Report Studio and SAS Add-In for Microsoft Office. • Graphs can be created as ActiveX (dynamic or image), Java Applets (dynamic or image), GIFs or JPEGs. ActiveX and Java Applets permit direct interaction with the graph objects without resubmitting requests to the server. • An intuitive process flow diagram facility allows users to visually organize and maintain their projects. • Easily extend the range of business problems that can be quickly solved with the development and deployment of custom tasks that appear alongside the core product functionality. Reporting, graphical and analytical tasks • Descriptive reports and analysis: basic listings, summary statistics tables, one-way frequencies tables, correlations tables and graphs, and tabular or graphical distribution analysis. • Graphs: area chart, bar chart, box plot, bubble plot, donut chart, line plot, map graph, pie chart, radar chart, scatter plot, surface plot and contour plot. • Analysis of Variance (ANOVA) predictive models: t-test, one-way ANOVA, nonparametric one-way ANOVA, linear models and mixed linear models. • Regression models: linear, logistic, nonlinear and generalized linear models. • Multivariate relationship models: cluster analysis, factor analysis, principal components, canonical correlation and discriminant function analysis. • Survival analysis: life table and proportional hazards. • Capability analysis: CDF plots, histograms, P-P plots, probability plots and Q-Q plots. • Control charts: mean and range, mean and standard deviation, individual measurements, box, p, np, u and c charts. • Pareto: Pareto charts. • Forecasting: data transformation, basic forecasting, ARIMA modeling and forecasting, regression analysis with autoregressive errors and regression analysis of panel data. • Table analysis. • Operations research: numerical optimization, algebraic modeling language, project and resource scheduling, generic algorithms and constraint programming. • Integration with SAS Rapid Predictive Modeler enables business analysts and subject-matter experts to quickly and efficiently create predictive models and step through a workflow of data preparation tasks.
  • How does it look like?
  • Example of an output, bar chart
  • If you are more familiar and/ or prefer programming, there is an advanced interface that allows you to do that keeping the code in the process flow, as part of your project and giving you an overall view of your work at all times.Programming Interface that can be used to write, edit, and submit SAS code.
  • More details about the interface.The project
  • More details about the interface.The project
  • Code is also generated in the background when you carry out a task. This allows you to go and customise the program to your preference.Improved productivity using the program editor with AUTOCOMPLETE and INTEGRATED SYNTAX for faster programming.
  • DATA MANAGEMENT • Visually access any data type supported by SAS and native Windows data types via ODBC, OLE DB, OLE DB for OLAP (specifically SAS OLAP Server, Microsoft Analysis Services and SAP BW), and from MS Exchange mail servers. Accessible local file types include: Microsoft Word documents (embeddable in project files to help document your project work), Excel, HTML, Access, Lotus 123, Paradox, .TXT files (fixed width), ASC files (ASCII), TAB delimited files and CSV files (comma delimited). • Allows easy access of data (local and remote) for use in other SAS products or JMP®. • Provides access to information maps created in SAS Information Map Studio. • Powerful, graphical query builder allows users to visually access and manipulate their data without SQL expertise: • Join up to 256 tables simultaneously.
  • This are the simple things that I am going to show you today. 1 through to 7 are quite simple but very powerful things that can used at any level to create reports, in real time that can be automated and run without requirement for updating, even though you can do so if you like.8 and 9 are slightly more specific statistical test that can be applied in the healthcare sector and I’ll show you a couple of examples if you like, and you can try some of the feasibility on your workstation later on.
  • These are all the types of data that you can import in SAS, pretty much everything
  • This task is one that you would use a lot. It allows you to generate frequency counts with percentanges, valid percentages, cumulative and so on. It can graph and provides some statistical tests to analyze the distribution of your data
  • These are all the types of graph that you can access and useHere are some examples
  • I wanted to show you this node because I think it is quite powerfulThis allows you to do an exploratory analysis of your dataset with no preconception of knowledge of what’s in it. It just presents you all data in accordance to its type and format. If categorical or nominal, it’ll show frequencies of classes, if interval or numeric, it’ll show you basic statistics such as range, min, max, mean, median, standard deviation.
  • This is also a very good report that you can tailor to give you the stats you prefer
  • In EG you can run some simple or complex models for example for linear regression
  • The objectives of a simple………
  • EG 4.3 will bring capabilities that help improve user productivity, enhanced integration and increased performance. With the previous release of EG 4.2, we saw the major improvements coming from the User Interface point of view – streamlined context specific menus, roles based User interface and new tasks. With the upcoming release of EG 4.3, you will see more of these coming with further enhancements aimed at both the worlds of coder and non-coders.Some of the key features provided are: New program editor with auto complete and integrated syntax helpEnhanced OLAP Analysis capabilities for enriched user experienceTighter integration with SAS WRS Reports and JMPRapid Predictive Modeling (RPM) Enterprise Miner integrationNew performance enhancement capabilities with Explicit SQL pass-through option, In-database optimized syntax generation and Integration for Grid enablement
  • SAS Enterprise Guide provides several capabilities targeted towards providing a highly productive and interactive interface for SAS programmers of all skill levels. Whether you are creating new programs or simply maintaining existing programs, this interface will provide all that is required for efficient programming and its maintenance.
  • Compared to Base SAS editor, the Program Editor of SAS Enterprise Guide comes with numerous capabilities and provides a user-friendly, interactive and intelligent SAS programming environment.It provides tooltips for SAS keywords including SAS PROCS, SAS functions and macro variables detailing the syntax, the description and the use. This capability comes handy for understanding existing SAS programs, for exploring different SAS programming options and removes the downtime one might go through while reaching out to books to find the same information.
  • The intelligence editor provides access to the complete catalogue of SAS PROCS and Functions that are readily available within the editor as the user keeps typing the program.Such capability not only provides appropriate options associated to a SAS keyword, they also help to generate a syntactically correct code from the beginning.
  • Users can also use other useful options such a code indentation for more readable coding practices
  • The interface provides option to convert the lines of code into Process Flow for visual representation and ease of understanding of the program flow.
  • There of couple of enhancements to the OLAPAnalyzer inside SAS Enterprise Guide designed to provide and enriched user experience.The Filter UI enhancements of EG 4.3 helps user to visually understand the way applying filters would work on the data with examples for each filter types.
  • The Enhanced MDX Editor makes it easy for the users with limited MDX skills. They can simple use the drag-n-drop feature to add the required metrics to their query which will automatically add the appropriate MDX syntax query.
  • For specific member values to be added to the query, the UI provides Search capability with number of pre-defined search criteria.
  • EG 4.3 now provides Automatic Charts for OLAP Analysis. This auto-charting capability provides the end user with a suitable graphical view of the data that fits best based on the selected Dimensions and Measures of analysis. New chart types – Tile Chart and Scatter Plots have been added for advanced graphical analysis.
  • This is an enhancement to existing Explorer view available with SAS EG.This option of “Apply Path to Siblings” is useful in smoothly navigating across members when moving from one dimension analysis to another (From Geography to Products as in example) making the analysis process faster.
  • Ability to directly send data from EG 4.3 to JMP for the additional dynamic analysis required by some business users.
  • This provides a complimentary approach for users getting a rapid, automated modeling engine and report generation process.
  • SAS Enterprise Guide continues its focus on providing end users with richer user experience and enhanced capabilities utilizing the power of the platform for SAS Business Analytics. Listed here are the key release objectives for the 5.1 release of SAS Enterprise Guide.Release ObjectivesLeverage the capabilities of SAS 9.3 platformEnriched User ExperienceIncreased productivityKey FeaturesEnhanced program editor with auto complete for data itemsImproved tooltip support for SAS keywords with help documentsEnhanced OLAP Analysis capabilities for enriched user experienceEnriched interface for creating Stored Process
  • The enhanced program editor in Enterprise Guide 5.1 brings the ability to view the variables from the selected data set from a library. This helps the users to rightly select the variables for analysing without worrying about the exact name of the variable. This boosts the programming speed of the user and helps generate a syntactically correct code, right from the start.
  • The optional tooltips for SAS keywords as were introduced in 4.3 release of Enterprise Guide are also enhanced supporting programmers to reach SAS documentation over the web for the associated SAS keyword helping users to stay focused within their working environment.
  • To help programmers to view sections from their large program in parallel, the enhanced editor brings the option to split the programming window and stack the windows side-by-side or tiled. This helps the user to view different sections of their program in a same view without the need to scroll all the way. Users can also copy program from one window to another if required.
  • For OLAP Analysis using the OLAP Analyzer in SAS Enterprise Guide, users can make use of pre-defined calculations based on time-series analysis.
  • With a more refined Contextual Menu, user can select which type of Totals and % of Totals they would like to view for their OLAP Data under analysis.
  • SAS Enterprise Guide 5.1 brings the capability inside Query Builder to save queries as Templates. This brings a big advantage of reusing the existing queries as sub-queries and hence avoids the efforts to recreate an existing business logic once again for a new query. This not only provides enriched user experience but also saves time and improves user productivity.
  • Not to teach SAS but rather to highlight how SAS contributes to the different aspects of study design, conduct, analysis, and reporting. With focus on analyzing data, specifically summarizing data, and some features that aid in the statistical reports. Mainly stating which SAS procedures are useful and show some examples of tables / figuresIntroduce a case study which I will use for illustration… restrospective psychiatric data from Duke US.Will also show some hypothetical examples for typical or noteworthy RCT settings
  • Transcript

    • 1. SAS HealthcareWorkshop 201118 November 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 2. Agenda 2.00 - 4.00pm : Statistical Analysis in Healthcare Industry showcasing SAS Enterprise Guide and SAS STAT capabilities in HealthCare analytics - Giuseppe Manai , SAS Senior Pre-sales Consultant - Jun Yao, SAS Pre-sales Consultant 4.00 - 4.15pm : Tea Break 4.15 - 5.15pm : Powerful Features of SAS: Reporting and Presenting Relevant Statistical Summary of Clinical Data - Dr Pryseley N. Assam, Adjunct Assistant Professor for Centre for Quantitative Medicine, Duke-NUS Graduate Medical School & Biostatistician at Singapore Clinical Research Institute 5.15 - 5.45pm : Application of PROC Frequency in Clinical Analysis - Mr Gabriel Jiang, Senior Statistician-Computation, Lilly-NUS Centre for Clinical Pharmacology Pte. Ltd. 5.45 - 6.00pm : Q&A and Closing 2SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 3. Statistical Analysis inHealthcare IndustryGiuseppe Manai, SAS Senior Pre-sales ConsultantJun Yao, SAS Pre-sales Consultant Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 4. Outline  SAS Business Analytics Framework Giuseppe  Introduction to SAS Enterprise Guide  SAS Enterprise Guide Workspace  Tasks and Wizards: Easy in Enterprise Guide  Examples + Hands-on Activity  Statistical techniques  Scheduling Jun Yao  What’s New in SAS Enterprise Guide 5.1 4SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 5. 5SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 6. How do we do it? 6SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 7. How do we do it? BUSINESS SOLUTIONS 7SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 8. How do we do it? INFORMATION MANAGEMENT 8SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 9. How do we do it? ANALYTICS 9SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 10. How do we do it? REPORTING 10SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 11. Healthcare Providers Using SAS Business Issues Facing problem in data integration and data analysis. Different software was being used in each department making consolidation of the data difficult to achieve or even visualise. Solution Integration of the clinical and medical management data analysis. Results Patient response times are much quicker and effective. 11SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 12. Healthcare Providers Using SAS Business Issues Large data analysis was slow and difficult. Separate software was being used in different departments causing problems with data integration and resulting in analytical limitations. Solution Integrates the different departments under a single repository of information enabling access to all in a standardised single version of the truth. Results standardized records and reports 12SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 13. Introduction to SAS Enterprise Guide 13SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 14. Introduction to Enterprise Guide Quick access and manipulation of data Carry out basic and complex analysis Easy to use basic reporting 14SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 15. Introduction to Enterprise Guide  What does SAS EG do?  Point-and-click GUI  Menu- and wizard- driven  Enables fast data analysis and results publishing  Fast-track learning data analysis  Generates code in background for productivity  Deploys analyses and forecasts in real time.  Who is SAS EG designed for?  Business analysts with no SAS programming experience  SAS programmers  Statisticians 15SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 16. Introduction to SAS Enterprise Guide Point-and-click interface for managing data and generating reports. 16SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 17. Introduction to SAS Enterprise Guide 17SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 18. Introduction to Enterprise Guide Programming Interface 18SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 19. SAS Enterprise Guide Interface A PROJECT is a single file that serves as a collection of:  Data sources  SAS programs and logs  Tasks and Queries  Results  Informational Notes for Documentation You can control contents, sequencing, and updating of a project. 19SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 20. SAS Enterprise Guide Interface 20SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 21. Behind the ScenesAs you build tasks, Enterprise Guide generates SAS code. 21SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 22. Tasks and Wizards: Easy in EG Data Management  Quickly Visualize, Open or Import Data  Join Datasets efficiently  Create Frequency Reports  Program Editor Visualization  Graphs (Histogram/ Bar-Chart/Pie Chart) Statistical techniques  t-test  ANOVA 22SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 23. Examples 23SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 24. Building a SAS Enterprise Guide Project 1. Add Datasets (can also import from Excel) 2. Perform a task 3. One-way frequencies and statistical tests 4. Automate a Process 5. Graphing 6. Create Reports (List Data) 7. Summary Statistics 8. Simple Linear Regression 9. t-Test and ANOVA 24SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 25. Common Data Formats  SAS datasets  Microsoft Excel and Access  DBMS tables  Text files  JMP  HTML  SPSS 25SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 26. One-Way Frequency Report The One-Way Frequencies task can be used to generate:  Frequency counts  Percentages  Graphs  Statistical tests to analyze the distribution of your data 26SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 27. Types of Graphs The Graph menu includes all of the advanced graph tasks as well as the wizards. 27SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 28. Graphs Using SAS Enterprise Guide 28SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 29. Characterize Data The Characterize Data task is an exploratory task that produces automatically statistics and graphs for all variables, grouping by type of variable (i.e. categorical, interval, etc.) 29SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 30. Summary Statistics Report  Calculate summary statistics based on groups within the data.  Can produce reports, graphs and data sets as output. 30SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 31. Automate a Process To automate a process flow you simply name it Autoexec This will run the process flow when opening the project 31SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 32. Hands-on activity (10-15 min) Try to:  Import a dataset  Create a task  Graph the results  Automate the process 32SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 33. Simple Linear Regression Analysis 33SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 34. Simple Linear Regression Analysis The objectives of simple linear regression are to:  Assess the significance of the predictor variable in explaining the variability or behavior of the response variable 34SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 35. Simple Linear Regression Model b1 units 1 unit b0 35SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 36. Simple Linear Regression Model 36SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 37. Performing Simple Linear Regression  Example …… 37SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 38. t-Test and ANOVA 38SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 39. Performing t-Test (Paired Sample) Analyze differences between two population means using the t-Test task. Perform a paired-sample t-test to determine whether a medication was successful in reducing blood pressure. 39SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 40. Scenario 1  Dataset To observe the effectiveness of a medication in reducing blood pressure, an experiment was conducted in which researchers collected data from a random sample of individuals who were considered to have high blood pressure. The diastolic blood pressure of these individuals was recorded, after which they were placed on the medication. One month later, their diastolic pressure was recorded again.  Objective Determine if the data gives good evidence that the medication was effective in reducing blood pressure by carrying out a test of significance (at level α = 0.05), pairing the two blood pressure recordings for each subject. 40SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 41. Performing Simple Linear Regression  Example …… 41SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 42. Analysis of Variance (One-Way ANOVA) Perform a one-way ANOVA to determine whether there are significant differences between four drugs in mean increase in systolic blood pressure. 42SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 43. Scenario 2  Dataset Consider a pharmaceutical company that has recently focused on the effect of its potential products on blood pressure. Researchers conducted a study in which the subjects were 72 individuals with one of three diseases. Eighteen individuals were randomly assigned to each of the four drugs. The treatments were administered over time and the increase in systolic blood pressure was recorded.  Objective Determine whether there are significant differences between the mean increases in systolic blood pressure for the four drugs. If there are, evaluate which drugs differ and how greatly they differ. 43SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 44. One-Way ANOVA  Example……. 44SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 45. Hands-on activity (10-15 min) Explore Enterprise Guide’s tasks  Use data sets provided  Modify variables  Use different tasks  Create graphs and reports 45SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 46. Task Scheduling via Enterprise Guide 46SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 47. What’s New in SASEnterprise Guide 4.3 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 48. SAS® Enterprise Guide 4.3  Release Objectives  User productivity  Integration  Performance  Key Features  New program editor with auto complete and integrated syntax help  Enhanced OLAP Analysis capabilities for enriched user experience  Tighter integration with SAS WRS Reports and JMP  Rapid Predictive Modeling (RPM) Enterprise Miner integration  New performance enhancement capabilities with Explicit SQL pass- through option, In-database optimized syntax generation and Integration for Grid enablement 48SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 49. Enhancements for SAS Programmers 49SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 50. Enhanced Program Editor Mouse over Tooltip with details for SAS PROCS, SAS Functions 50SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 51. Enhanced Program Editor - Autocomplete Connects to data library listing accessible data tables Provides list of SAS PROCS, SAS Functions and Macro variables, assisting user while coding 51SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 52. Enhanced Program Editor Converts code into Indented Format 52SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 53. Enhanced Program Editor – Analyze Program Coverts lines of Code into Process Flow for visual representation and ease understanding of the program flow 53SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 54. Adhoc Analysis Enhancements 54SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 55. OLAP Analyzer – Enhanced Filtering options Enhanced filter options with Example support 55SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 56. OLAP Analyzer - Enhanced MDX Editor • Drag-n-Drop support to add measures/dimensions to the MDX • Show Line numbers for MDX 56SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 57. OLAP Analyzer - Enhanced MDX Editor New options for Search 57SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 58. OLAP Analyzer - New Chart Types New Chart Types • Scatter Plot • Tile Chart • Automatic Charting (creates a chart based on Dimensions and Measures selected in crosstab) 58SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 59. OLAP Analyzer – Enhanced Explorer View Apply Path to Siblings option for a smoother data exploration experience. 59SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 60. Integration with JMP Data opened in EG 4.3 Data opened in JMP 60SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 61. Integration with Rapid Predictive Modeler Self service analysis and report generation using wizard driven RPM task 61SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 62. What’s New in SASEnterprise Guide 5.1 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 63. SAS® Enterprise Guide 5.1  Release Objectives  Leverage the capabilities of SAS 9.3 platform  Enriched User Experience  Increased productivity  Key Features  Enhanced program editor with auto complete for dataset variables  Improved tooltip support for SAS keywords with help documents  Enhanced OLAP Analysis capabilities for enriched user experience  Reusable queries (Query Templates and Sub Queries)  Enriched interface for creating Stored Process 63SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 64. Enhanced Program Editor Enriched user experience and increased productivity Provides the ability to view the list of variables from the selected data set. 64SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 65. Enhanced Program Editor Enriched user experience and increased productivity Enhanced tool tip support with web link to Product Documentation and Samples. 65SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 66. Enhanced Program Editor Enriched user experience and increased productivity Ability to split and stack the programming window – side by side or tiled • Work with different parts of same program in single view 66SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 67. Adhoc OLAP Analysis Enriched user experience Predefined Calculation Functions for time-series data analysis 67SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 68. Adhoc OLAP Analysis Enriched user experience Refined Contextual Menu for defining Totals and % of Totals 68SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 69. Reusable Queries 1  Define queries and save them as Templates 2  Use existing queries as Sub- Queries to filter data 69SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 70. Options for Code Submissions Ability to define the Code Submission options and gain increased performance in a grid enabled environment 70SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 71. Any Questions? 71SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 72. Tea-Break 72SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 73. SAS Healthcare WorkshopPowerful SAS Features:Reporting & PresentingStatistical Summary ofClinical DataPryseley Assam (PhD)Biostatistician, Singapore Clinical ResearchInstituteAssistant Professor, Duke-NUS GraduateMedical School Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 74. Outline  Introduction  A case study – retrospective study  Some useful SAS features (summaries, reports)  Remarks 74SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 75. Introduction  Mandatory Clinical Trial Registration » The International Committee of Medical Journal Editors » Pharmaceutical Research & Manufacturers of America  New England Journal of Medicine (Sept 16 issue 2004) … patients have a right to trust that investigators will not only minimize risks to the participants but also will conduct research ethically and report it completely and honestly. 75SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 76. Introduction  Obligation to report/publish research findings » Participants (patients) » Scientific committee » Sponsors  Guidelines for reporting » Randomized controlled trials: CONSORT » Systematic reviews and meta-analysis: PRISMA » Observations studies: STROBE » Diagnostic studies: STARD 76SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 77. Introduction  Complete and honest reporting is facilitated by appropriate study design, conduct and analysis, in accordance with the study objectives Increasing demand for statistical input in healthcare studies 77SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 78. Introduction  Statistical report » Design, size, and outcomes of the study » Patient selection flow chart Statistical data review » Summary statistics » Graphs » Analysis  Automated summaries and report attributes 78SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 79. Case Study - DUMIN  Motivation » RCTs are not representative of practice » Strict measurement based-care approach » Higher doses than found in typical clinical care  Data description » All outpatients with clinical depression (and anxiety) » On one antidepressant medication for at least 1week » At least two assessment within the 9 weeks of treatment » Study period: January 2000 to December 2010 79SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 80. Case Study - DUMIN  Objectives  Describe overall response rates » CGI-I » CGI-S change from baseline  Is outcome related to » Baseline severity » Duration of treatment  Identify clinical features associated with outcomes 80SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 81. Some useful SAS FeaturesSummarizing Data Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 82. Summarizing Data  Listings » Useful for providing detail reports; a detail report gives you at least one row of information in your report for selected observations (patients/events) in the data set. » Reporting severe adverse events in RCT » DATA Steps, PROC TRANSPOSE, PROC SQL » PROC PRINT, PROC REPORT 82SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 83. Summarizing Data  Listings  Enhancements » Labels of variables (DATA steps, PROC SQL) » Formats for values of variables (PROC FORMAT) » Styles and templates 83SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 84. Summarizing Data  Listings » Suicidal patients – PROC PRINT (WHERE clause) 84SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 85. Summarizing Data  Listings PROC FORMAT; VALUE $ SexF "M" = "Male" "F" = "Female" ; RUN; PROC PRINT DATA=LOC.Dumin (FIRSTOBS=1 OBS=25) NOOBS LABEL BLANKLINE=5 N; FORMAT Gender $SexF.; WHERE Suicide = "Yes"; VAR BackgroundID Gender Race2 Age_Bin Diagnosed Suicide Mono Med_Class Substance Subst ; RUN; 85SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 86. Summarizing Data  Listings 86SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 87. Summarizing Data  Listings » Suicidal patients with ≥ 2 assessments – PROC SQL PROC SQL; CREATE TABLE Suic_2 AS SELECT DISTINCT BackgroundID, Gender, Race2, Age_Bin, Diagnosed, Suicide, Mono, Med_Class, Substance, Subst, Suicide FROM LOC.Dumin WHERE BackgroundID IN (SELECT DISTINCT BackgroundID FROM LOC.Visits GROUP BY BackgroundID HAVING COUNT(ENum) > 2 ) ; QUIT; 87SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 88. Summarizing Data  Listings » Suicidal patients with ≥ 2 assessments – PROC SQL 88SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 89. Summarizing Data  Listings » Safety analysis in RCTs First dose date Onset date Preferred Investigator Relation Trt ID Visit /Last dose /Resolution System Organ Class to study given /Grp No. Term Term date date drug to AE 02JUL2011 / 01JUL2011 / GIDDINESS FOR 31356 / A V2 Nervous system disorders Dizziness Unknown No 12AUG2011 01JUL2011 HOURS1356 / 02JUL2011 / 01JUL2011 / DAY-TIME V2 Psychiatric disorders Somnolence Unknown NoA 12AUG2011 05JUL2011 DROWSINESS1356 / 02JUL2011 / 30JUL2011 / DAY-TIME V6 Psychiatric disorders Somnolence Likely NoA 12AUG2011 03AUG2011 DROWSINESS General disorders and 23SEP2011 / 07OCT2011 / Not1463 / B V3 administration site Feeling hot WARM SENSATION No 16NOV2011 07OCT2011 related conditions Musculoskeletal and 23SEP2011 / Not1463 / B V4 19OCT2011 / . connective tissue Arthralgia LEFT ANKLE PAIN No 16NOV2011 related disorders 89SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 90. Summarizing Data  Summary report » A summary report generally does some form of collapsing of observations so that each row in the report represents information from more than one observation » Demographic and baseline clinical characteristics » Efficacy and safety outcomes » PROC SQL, MEANS, SUMMARY, FREQ, UNIVARIATE » PROC TABULATE, REPORT, TRANSPOSE 90SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 91. Basic Summary  Outcomes – PROC MEANS PROC MEANS DATA=LOC.Dumin MISSING N NMISS MEAN STD MIN MAX NONOBS MAXDEC=3; CLASS Suicide; VAR CGI_Entry CGI_1 CGI_2; RUN; 91SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 92. Basic Summary  Demographics – PROC FREQ PROC FREQ DATA=LOC.Dumin; TABLE Gender Age_Bin Race2 Diagnosed ; RUN; 92SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 93. Basic Summary  Demographics – PROC FREQ PROC FREQ DATA=LOC.Dumin; TABLE Gender Age_Bin Race2 Diagnosed / MISSING ; RUN; 93SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 94. Basic Summary  Demographics – PROC FREQPROC FREQ DATA=LOC.Dumin ORDER=INTERNAL; TABLE CGI_1 / MISSING OUT=CGI OUTCUM; TABLE Suicide*CGI_1 / MISSING OUT=CGIS OUTPCT; TABLE Diagnosed*CGI_2 / MISSING OUT=CGIS OUTPCT;RUN; 94SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 95. Summary Tables  PROC TABULATE » Very useful descriptive statistics » Simple but powerful methods to create tabular reports » Establishing hierarchical relationships between the variables » Mechanisms for labeling and formatting variables and procedure- generated statistics. 95SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 96. Summary Tables  Tables of summary statistics - TABULATE PROC TABULATE DATA=LOC.Dumin ORDER=FREQ; CLASS Gender Age_Bin Subst Race2 Med_Class Mono ; VAR CGI_1; TABLE ALL="All Patients" Gender Age_Bin Med_Class*Mono Subst Race2 , ALL="All Patients"*(N REPPCTN="%") CGI_1*(MEAN STD LCLM UCLM); RUN; 96SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 97. Summary Tables  Continuous outcome - TABULATE 97SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 98. Summary Tables  Continuous outcome - TABULATE DATA LOC.Dumin; SET LOC.Dumin; Sex = "Gender"; Races = "Race"; AgeGrp = "Age Groups"; SuicP = "Suicidality"; RUN; PROC TABULATE DATA=LOC.Dumin MISSING ORDER=FREQ; FORMAT Suicide $Sui.; CLASS Gender Age_Bin Race2 Suicide Sex Races AgeGrp SuicP ; VAR CGI_1; TABLE ALL="All Patients" Sex*Gender AgeGrp*Age_Bin Races*Race2 SuicP*Suicide , ALL="All Patients"*(N REPPCTN="%") CGI_1*(MEAN STD LCLM UCLM) /RTS=25 INDENT=4 ; RUN; 98SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 99. Summary Tables  Continuous outcome - TABULATE 99SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 100. Summary Tables  Binary outcome - TABULATE PROC FORMAT; VALUE CGIIB 1 - 3 = "Improvement" 4 - 7 = "No Improvement" Other = " " ; RUN; PROC TABULATE DATA=LOC.Dumin MISSING ORDER=FREQ; FORMAT CGI_1 CGIIB.; CLASS CGI_1 Gender Race2 Age_Bin Subst Sex Races AgeGrp ASubs ; TABLE ALL="All Patients" Sex*Gender AgeGrp*Age_Bin Races*Race2 ASubs*Subst , ALL="All Patients"*(N REPPCTN="%") CGI_1*(N REPPCTN="%") /RTS=25 INDENT=4 ; RUN; 100SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 101. Summary Tables  Cell Percentages - TABULATE 101SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 102. Summary Tables  Row Percentages - TABULATE PROC TABULATE DATA=LOC.Dumin MISSING ORDER=FREQ; FORMAT CGI_1 CGIIB.; CLASS CGI_1 Gender Race2 Age_Bin Subst Sex Races AgeGrp ASubs ; TABLE ALL="All Patients" Sex*Gender AgeGrp*Age_Bin Races*Race2 ASubs*Subst , ALL="All Patients"*(N REPPCTN="%") CGI_1*(N ROWPCTN="%") /RTS=25 INDENT=4 ; RUN; » Useful for comparison 102SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 103. Summary Tables  Row Percentages - TABULATE 103SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 104. Summary Tables  Proportions of Covariates - TABULATE Direct cost What are the respective contributions of the components of direct cost and the type of cases to the total direct cost? 104SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 105. Summary Tables  Proportions of Covariates - TABULATE PROC TRANSPOSE PROC TABULATE DATA=LOC.H_Expend FORMAT=8.2; WHERE Cost = "Direct"; CLASS CT Cost CC; VAR Value; TABLE CC* (Sum=Cost per Case PCTSUM<CC>=% by Direct Cost PCTSUM<CT>=% by Case Type PCTSUM=Overall %) , Value*CT /RTS=35 INDENT=4; RUN; 105SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 106. Summary Tables  Proportions of Covariates - TABULATE 106SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 107. Saving Outputs  ODS RTF (Rich text format) » Editable reports (manuscripts)  ODS PDF » Non-editable reports » Validation results, Safety and protocol deviations  ODS HTML » Websites 107SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 108. Saving Outputs  Basics X “CD C:SAS HealthCare WorkshopFigures”; ODS RTF File=“File Name.rtf"; SAS PROCEDURES ODS RTF CLOSE; OPTIONS ORIENTATION=LANDSCAPE ODS RTF File=“File Name.rtf“ STYLE=myStyle; TITLE ; TITLE2 ; ODS TEXT=“Include Text”; SAS PROCEDURES ODS RTF CLOSE; 108SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 109. Outputs for Reports  Stored RFT Files (Templates) 109SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 110. Outputs for Reports  Style = + FORMAT Journal 110SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 111. Summary Reports  Employing multiple procedures, styles and format » PROC MEANS, UNIVARIATE, FREQ, … » PROC TABULATE, PROC REPORT » ODS RTF » OPTIONS Statement » MACROS » … 112SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 112. Automated Summary Reports 113SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 113. Automated Summary Reports 114SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 114. Some useful SASFeaturesDepicting Data Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 115. Depicting Data Graphical representations of data are often more easily understood and remembered than tabular forms  SAS GRAPH - Procedures » SGPLOT, SGPANEL, SGSCATTER, … » GREPLAY  ODS Graphics (over 60 procedures) » SAS/Base » SAS/STAT, SAS/ETS, SAS/QC 116SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 116. Depicting Data ODS Graphics ON Procedure options Default plot created PLOTS=syntax [non-default plots] ODS Graphics OFF 117SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 117. Depicting Results  Regression diagnostics - Example 118SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 118. Depicting Data  Basic things to note for ODS Graphics X "CD C:SAS HealthCare WorkshopFigures"; ODS GRAPHICS ON / IMAGENAME="MyFigure" IMAGEFMT=; GRAPH/STAT PROCEDURE DATA= ; PROCEDURE OPTIONS RUN; ODS GRAPHICS OFF;  Formats (IMAGEFMT=) » PNG, PS, TIFF » JPEG, GIF, PDF, WMF 119SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 119. Depicting Data - DUMIN  Patient selection 18475 patients 1722 (9%) Eligible patients 120SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 120. Depicting Data - DUMIN  Primary outcome (CGI-I) Requested plot Final plot » INSET and FORMAT statements 121SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 121. Depicting Data - DUMIN  Primary outcome (CGI-I) PROC FREQ + SGPANEL SGPANEL 122SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 122. Depicting Data - DUMIN  Primary outcome (CGI-I) 123SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 123. Depicting Data  Multiple graphs in a figure » PROC GREPLAY 124SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 124. Depicting Data - DUMIN  CGI outcomes » IMAGEFMT=PS and LaTeX 125SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 125. Depicting Data  Absolute and cumulative percentages FREQ + SGPLOT 126SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 126. Remarks  Reporting results of clinical studies is mandatory  Results need to be represented concisely and precisely Having the right tools is important!  SAS provides extensive tools for summarizing data and preparing results for reporting, especially when used in conjunction with other software » Use the SAS thoughtfully 127SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 127. Any Questions? 128SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 128. SAS Healthcare Workshop 2011Application of PROCFrequency in ClinicalAnalysisGabriel JiangSenior Statistician-Computation, Lilly-NUSCentre for Clinical Pharmacology Pte. Ltd. Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 129. PROC FREQ  What else can we do other than counting observations and putting them in cross tabulation or n x n ways?  Common syntax PROC FREQ <options> ; BY variables ; EXACT statistic-options </ computation-options> ; OUTPUT <OUT=SAS-data-set> options ; TABLES requests </ options> ; TEST options ; WEIGHT variable </ option> ; run; 130SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 130. PROC FREQ  Agenda - Filling in zeroes with Sparse Option - Complement with ODS Graphics - Controlling displayed output 131SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 131. PROC FREQ (1)  Scenario: I need to have lots of ‘0’ values in my tables, to show that there were no event occurrences 132SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 132. PROC FREQ (1) Example Lots of zeroes 133SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 133. PROC FREQ  Solution? You can create zeroes in a dummy dataset, and proceed to merge with the original ‘incomplete’ dataset  Another question: It’s troublesome to create the dummy dataset, I don’t even know which combinations are missing 134SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 134. PROC FREQ  Solution: If you are using PROC FREQ, then there is an easy solution Use the SPARSE Option! 135SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 135. PROC FREQ Sample code Original code: proc freq data=heart1; table sex*chol_status*weight_status/ out=all noprint; run; New addition: proc freq data=heart1; table sex*chol_status*weight_status/ out=all sparse noprint; run; #Using data from SASHELP.HEART 136SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 136. PROC FREQ Previously missing combinations of Sex, Cholesterol Status and Weight Status Observations with missing Cholesterol Status 137SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 137. PROC FREQ Output without the Sparse option Missing zero Combinations incomplete 138SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 138. PROC FREQ Final Output Cholesterol Status is missing Previously, combination of categories that were not available 139SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 139. PROC FREQ (2)  Scenario: I don’t want to have to write a whole set of GPLOT statements to get plots from PROC FREQ outputs, what should I do? 140SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 140. PROC FREQ SAS/Graph? Maybe by using PROC GPLOT? PROC GPLOT <DATA=input-data-set> <ANNOTATE=Annotate-data-set> <GOUT=<libref.>output-catalog> <IMAGEMAP=output-data-set > <UNIFORM>; BUBBLE plot-request(s) </option(s)>; BUBBLE2 plot-request(s) </option(s)>; PLOT plot-request(s) </option(s)>; PLOT2 plot-request(s) </option(s)>; 141SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 141. Combining with ODS Graphics ODS GRAPHICS ON; PROC FREQ <options> ; BY variables ; EXACT statistic-options </ computation-options> ; OUTPUT <OUT=SAS-data-set> options ; TABLES requests / PLOTS < ( global-plot-options ) > < = plot- request < ( plot-options ) > > ; TEST options ; WEIGHT variable </ option> ; run; ODS GRAPHICS OFF; 142SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 142. Combining with ODS Graphics  Plots 143SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 143. PROC FREQ Sample Code ods graphics on; proc freq data=heart; table sex*chol_status*weight_status/ plots(only)=freqplot; run; ods graphics off; 144SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 144. PROC FREQ Sample Output table sex*chol_status*weight_status/ plots(only)=freqplot(orient=vertical); 145SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 145. PROC FREQ Sample Output table sex*chol_status*weight_status/ plots(only)=freqplot(orient=horizontal); 146SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 146. table sex*chol_status*weight_status/ plots(only)=freqplot(orient=horizontal scale=freq|log|percent|sqrt type=barchart); 147SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 147. PROC FREQ table sex*chol_status*weight_status/ plots(only)=freqplot(orient=vertical scale=freq type=dotplot); 148SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 148. PROC FREQ Cumulative Frequency Plot Deviation Plot table sex/ table sex/ chisq plots(only)=cumfreqplo plots(only)=deviationplot( t(orient=horizontal scale=freq); orient=horizontal); 149SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 149. Frequency plots for multi-way tables plots(only)=freqplot(orient=horizontal twoway=groupvertical); plots(only)=freqplot(orient=horizontal twoway=grouphorizontal); plots(only)=freqplot(orient=horizontal twoway=stacked type=barchart); plots(only)=freqplot(orient=horizontal twoway=stacked type=dotplot); 150SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 150. Kappa plots plots(only)=kappaplot (npanelpos=0);c plots(only)=kappaplot (npanelpos=0 stats); plots(only)=kappaplot (npanelpos=1); 151SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 151. Kappa plots plots(only)=kappaplot(npanelpos=0 order=descending stats); plots(only)=kappaplot(npanelpos=0 order=ascending stats); plots(only)=kappaplot(npanelpos=0 order=ascending stats range=clip); plots(only)=kappaplot(npanelpos=0 order=ascending stats range=(-0.1,0.0)); 152SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 152. PROC FREQ Kappa plot Weighted Kappa plot plots(only)=kappaplot(npanelpos=0); plots(only)=wtkappaplot(npanelpos=0); 153SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 153. Odds Ratio Plot plots(only)=oddsratioplot(npanelpos=0 stats); plots(only)=oddsratioplot(npanelpos=0 logbase=10 stats); plots(only)=oddsratioplot(npanelpos=0 logbase=2 stats); plots(only)=oddsratioplot(npanelpos=0 logbase=e stats); 154SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 154. PROC FREQ (3)  Scenario: I have generated some outputs using PROC FREQ… how can I change the format of the values? 155SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 155. PROC FREQ Using the FORMAT= option Note: The FORMAT= option applies only to cross- tabulation tables displayed in the default format. It does not apply to cross-tabulation tables produced with the LIST or CROSSLIST option. For one way tables, you have to use PROC TEMPLATE 156SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 156. PROC FREQ Default (BEST6./BEST7.) proc freq data=heart; table sex*chol_status*weight_status / nopercent norow nocol ; run; 157SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 157. PROC FREQ Using Format= option proc freq data=heart; table sex*chol_status*weight_status / nopercent norow nocol format=12.3; run; 158SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 158. PROC FREQ  Question: If I want the layout as a list? 159SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 159. PROC FREQ Using LIST option proc freq data=heart; table sex*chol_status*weight_status / nopercent norow nocol list; run; 160SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 160. 161SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 161. References Base SAS® 9.2 Procedures Guide Statistical Procedures 3rd Edition http://bit.ly/bcT6Yt SAS 9.2 Online Documentation http://support.sas.com/documentation/cdl_main/index.html Chris Moriak (2002) , The Sparse Option in PROC FREQ: Little Known, Yet Powerful, NESUG15 Mike Rhoads (2009), Changing the Numeric Format of PROC FREQ Output http://support.sas.com/kb/24/822.html 162SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 162. Any Questions? 163SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.
    • 163. Thank you for your participation in SAS Healthcare Workshop 2011! Have A Great Day! If you have any further questions, you may email to Valeria Tan, Account Manager for Healthcare Sector at valeria.tan@sas.com Customer Success Team at customer.success@sas.com 164SAS Healthcare Workshop 2011 Copyright © 2011, SAS Institute Inc. All rights reserved.