VIEWS 2001 Papers - Index

44 papers. Source: VIEWS (International SAS Programmer Community) conference proceedings.

go 2003

#	Title ×	Authors ×	Abstract ×	Keywords ×	Extras	Pages
1	A Conjoint-based Choice Modelling Approach Using the PHREG Procedure to Evaluate the Importance of Fisheries Management Objectives	Premachandra Wattage, Simon Mardle, Sean Pascoe	Experimental modelling to identify the preference structures of management objectives in fisheries management is vital in a sustainable fisheries policy. Furthermore, identification of differences of preferences amongst stakeholders on these objectives provides a basis to justify direction within policy management. In this paper, a conjoint-based choice modelling approach is used to evaluate several overriding fisheries management objectives using the UK fisheries of the English Channel as an example. Using the SAS System, the multinomial logit model is fitted with the `SAS/STAT` `PROCEDURE PHREG` (proportional hazard regression) to identify the importance of fisheries management objectives. The likelihood function of the multinomial logit model has the same form as a survival analysis model fitted using the `PROC PHREG`	conjoint analysis, proc phreg, likelihood function, sample, null hypothesis, maximum likelihood estimation, logistic regression, predictor variable, estimate, p-value, regression analysis, main effect		14
2	An End To End Personalisation Framework For Multi Channels	Turlough Fitzpatrick	Presentation			22
3	Are You at Odds with ODS?	Philip R. Holland	The introduction of the Output Delivery System (`ODS`) in the SAS System version 7 gave programmers a consistent mechanism for formatting output from SAS Procedures and Data steps to printers and HTML. The defaults provided by `ODS` are more than adequate for formatting simple reports, but are not necessarily ideal for other types of reports, particularly if standards exist for company reporting. This paper will discuss the different options for customising and standardising `ODS`-formatted HTML reports, using examples for `PROC REPORT`, `PROC TABULATE` and the `DATA STEP`.			13
4	Closing the Loop - Using SAS to Drive CRM	Anton Hirschowitz	Customer Insight underpins Customer Relationship Management (CRM). Without a detailed understanding of customer profiles and behaviour, any CRM undertaking will be running blind. Conversely, no matter how sophisticated your Data Mining capability, Customer Insight will deliver little value without the processes in place that exploit the insight to build stronger customer relationships. This paper illustrates how SAS can be used to deploy Customer Insight throughout your organisation and examines how to plan for integration at the outset of your data mining projects. We also look at some of the techniques and tools available to organisations that transform Customer Insight into added customer value. These allow marketers to run and monitor large numbers of micro-campaigns, with individually customised messages delivered to customers through the most appropriate channels. By deploying Customer Insight the customer interaction systems ("touchpoints") and enabling ongoing analysis of communication performance and effectiveness, the CRM loop is closed.	data warehouse, campaign response, propensity score, data mining		13
5	Coding Across the Boundaries	David H. Johnson	One of the challenges facing a consultant in the SAS System is the need to deliver a 'fast start' on a new contract. One of the ways to achieve this, is to start an assignment with a toolkit of common utilities. If a utility is developed for the Windows platform to find and store the characteristics of files, a similar macro can be developed for the Unix or OS/390 environments. If the same name and set of parameters is used for the macro on each platform, then programs developed around the macro for one platform can be quickly deployed to a different platform. This allows the consultant to more quickly focus their attention on the main variable between assignments: the nature and structure of the business data	macro definition, if-then-else		13
6	Communication-Effective and - Efficient Enterprise Performance Reporting	LeRoy Bessler	The need for, and existence of, Enterprise Performance Reporting (EPR) long antedates the Balanced Scorecard concept and SAS Strategic Vision. I created my first EPR system about fifteen years ago, with Base SAS, `SAS/GRAPH`, and SAS macro language (the most useful second language for any SAS programmer), and have been fine-tuning my ideas and tools for SAS- and `SAS/GRAPH`-enabled reporting ever since. This paper first discusses some simple design concepts that can be applied in any EPR application, and probably in any reporting applications with a similar function, but less grand functional description. Today, the concepts certainly seem trivial and obvious, now that we have the convenient and quick hyperlinked drilldown paradigm of the web. But they weren't apparent to the builders of the system that I replaced.	macro loop, sample, bar chart, macro conditional, macro definition, proc step, line chart		20
7	Customising the Version 8 Environment	Simon Williams	With the advent of Version 8 for the SAS System it has become possible to customise various aspects of the user interface. The enhanced editor provides the functionality for coloured coded programs. Keywords, formats, quoted strings and numbers are just some of the aspects that we can colour. The docking views allow us to keep certain windows on display at all times. The Output Delivery System (`ODS`) can produce reports against the company logo or colour scheme via `PROC TEMPLATE`. The question is what should we as programmers change and how do we do it. This paper is intended for anyone interested in customising part of his or her SAS interface within the Windows environment	proc template, sas output, proc step		8
8	Data Mining and Statistical Models in Marketing Campaigns of BT Retail	Francesco Vivarelli, Martyn Johnson	In this paper we present some applications we develop to support marketing campaigns of BT Retail Consumer Division by using data mining techniques and statistical modelling to segment and build propensity models for our 19.5M base of customers. The base of customer has been segmented by K-means clustering algorithm, where location and width of the K Gaussian were optimized with the Expectation-Maximization algorithm. The 19.5M customers have been clustered on the basis of transactional summaries, demographic and lifestyle variables; balance of these features guarantees that segments are logical across each type of variable. We also build propensity models to optimise the selection of suitable customers who will be more likely to positively respond to marketing campaigns. We show how decision trees, logistic regression and neural networks score our base of customers by using traffic and billing data as well as demographic and lifestyle features. All our applications have been developed using the SAS System (release 8.2) for Microsoft Windows 98 (2nd edition) and release 4.1 of the Enterprise Miner Software.	neural network, sample, data mining, proc hpsplit, test set, logistic regression, regression analysis, data cleaning, binary variable, customer segmentation, prior probability, p-value, logistic distribution, missing value		9
9	Delivering Clinical Study Data Using SAS/IntrNet	Robert Davis, Barrie Nelson	Newly adopted FDA guidelines require clinical study data be delivered as SAS data files in all electronic submissions. The speed and depth at which Clinical Scientists need to assimilate this data is ever increasing. SmithKline Beecham, utilizing `SAS/INTRNET` technology, has developed a Patient Data Browser to address this need. This presentation will describe the Patient Data Browser and how `SAS/INTRNET` was employed. Topics will include the following: Patient Data Browser Overview Customer Requirements Regulatory Requirements Technical Requirements Application Security Overcoming SAS 6.12 and `SAS/INTRNET` 1.2 Limitations * Functional Overview	macro variable, clinical data	presentation	4
10	Develop in GUI, Run with Grunt	David H. Johnson	Development and testing of code is usually simplified by working in a Windows or similar Graphical User Interface (GUI) environment. The results of individual steps can be checked, and additional analysis performed on the data before further manipulation is performed. Problems in the code can be resolved and a final code version developed that is both tuned for performance, and robust enough for the production environment. However, the quantity of data that may be manipulated in a production environment is sometimes too large for the Windows platform. So the production process may need to be run on a mid range or mainframe platform	cpu time, proc step, macro variable, macro put, macro function, sample, %if-%then-%else, proc freq		8
11	Effective Strategies for Data Warehousing	Katie Essam	Presentation	proof of concept, data mart, sas base		19
12	Enterprise Guide - First Impressions	Bernadette Ruane	Over the last 5 years OCS has been providing a Helpdesk service to the Credit Risk Team of a large UK Bank. At the beginning of year, as part of this service, OCS were to extend the systems support provided by reviewing an existing application that provided a series of standard reports and to suggest improvements. The main benefits sought were a reduction in resources, increased flexibility in the generation and presentation of the reports and to have a broader dissemination option.	sas enterprise guide, excel	presentation	3
13	Enterprise Guide - The New Features in Version 1.2	Jeremy Rankcom	Presentation	sas enterprise guide, bar chart, data warehouse, missing value, dataset, big data, record count		16
14	From Data Entry to e-submission - only a button away with SAS. Integrated Clinical trial reporting - Oracle Clinical, SAS and Documentum	Andrew Lawton, Michael Pearce	Presentation	21 cfr part 11, sas output, macro variable, macro facility, catalog, dataset, data cleaning		16
15	How the Output Delivery System made UCAS Data 'Sing'	Gaie Davidson-Burnet, Liz Peters, Richard Coleman	Prospective students wishing to apply for entrance to universities and colleges in England, Wales, Scotland and Northern Ireland have been able to apply through a single central organisation to which they pay one fee for over three decades. Similarly, when students applied to study courses offered by polytechnics, they also applied through a single agency. Following the 1992 Education Act, the two bodies: the Universities Central Council on Admissions (UCCA) and the Polytechnics and Colleges Admissions Service (PCAS) were joined to form the Universities and Colleges Admissions Service: UCAS.	output delivery system, proc step		8
16	INFACT - A Web Based Solutio to Meeting the Demands for Public Access to Data Collections at the Public Expense	Carol Calvert	This paper outlines the design, development and implementation of two related projects. Both projects relate to the same large data collection; one deals with the collection of the data and the other with its publication. Both projects use SAS IntrNet, web browsers, and JAVA. The collection facility allows secure access to our data providers for data submission and checking. Data is run against SAS programs and error reports are produced immediately for the provider. The data provider uses the error report to correct their data and resubmits data files until there are no errors. At this stage data is loaded into the master data file for the collection. The publication facility allows the user to access a simple analysis tool and use this to define tables and charts of information that they require. The tables are not predefined but are generated in response to the specification by the user. Access is open to anyone with a web browser. Both projects were developed with edina software who are an Edinburgh software firm.	dataset, data cleaning	presentation	12
17	Is it Harder for a Pharmaceutical Company to Move from SAS V6.12 to V8.2 than it is for a Country to Qualify for the World Cup?	Gary Kennedy	Presentation			27
18	Knowledge Discovery and Data Mining Applied to Engineering Applications	Shirley Williams	Presentation	data mining, proc hpsplit, outlier, regression analysis		22
19	Making Database QC easy, the PAREXEL way	Oliver Rees	Presentation	dataset, data governance, data cleaning, sample, proc print, sas log, biostatistics		27
20	Managing Supplier Relationships In The E-World: The Need For Information	Jennifer Major, Trevor Payne	Presentation	output delivery system, customer satisfaction, data mart, data validation rules, data standard, data cleaning, ods html		59
21	Methods Of Building an Enterprise Layer to Help Data Exploitation and Delivery	Andrew Wilcox	This paper will discuss the possible options available to the SAS programmer when developing an enterprise or exploitation layer for a SAS data warehouse. Methods of using SAS Enterprise Guide, SAS Enterprise miner, SAS Enterprise reporter, Base SAS software combined with indexing techniques, `SAS/MDDB` Server Software and (or) Scalable Performance Data Server, will be discussed highlighting the efficiency drawbacks and benefits to implementing a successful reporting solution	dataset, proc step, sas base, proc means, proc sql, data mining, data warehouse, proc append, sas enterprise guide, libname statement, where statement, view, excel		23
22	Parallel Processing and Multi-Tasking in SAS before V9	Peter Crawford	Presentation			12
23	Processing Free Text With SAS Version 8	Jeremy Gurney	Presentation	dataset, numeric variable, clinical trial		31
24	Producing HTML Output Easy as ODS!	Stephen Hanks	Presentation	sas output, proc template, proc step		24
25	Providing SAS with a Voice	Pankaj Mistry	Presentation			22
26	Remote Data Querying	Richard Underwood	Presentation	data cleaning, sas base		13
27	SAS IntrNet, Wireless Computing	Peter Hobart	Presentation	data step, capacity planning, resource allocation, sas programming, sample		46
28	SAS MSc Business Intelligence: A Flexible Approach	Christine Straker, Tony Tricker	The Masters Course in Business Intelligence was set up due to industry demand and was designed to address the current skill shortage by combining education and SAS training. This paper will give a brief outline of the structure and content of the course along with a reflection on the first year of delivery in full time mode. The main focus of the paper will outline the design of a new part time MSc which incorporates the flexibility required to allow students to study whilst in employment	business intelligence, data mining		12
29	SAS Standard Reporting Application for e-Publication of MS Office Documents	Simon Pickles	A important component of the Data Warehouse is the production and distribution of high quality Static Reports that can be read by any member of the company with a standard desktop set up. This paper describes a SAS application that schedules the production of sophisticated reports in MS Office format and distributes them via email or on company Intranet to Business community. This is a mainly technical paper concentrating on the application design and programming techniques used. The techniques discussed will be mainly SAS BASE, AF and `EXCEL` OLE Automation although other areas will be mentioned (DDE, SAS `ODS`, JAVA and ASP Pages). SAS Platforms are Windows NT and Unix in Client Server mode	excel, name range list		13
30	SAS/AF Application in Sequential Clinical Trials	Tatsuru Matsushita	Competition in pharmaceutical drug development is intense. Planning and conducting clinical trials to confirm drug efficacy is a complicated procedure, and software aids are very desirable for those managing this activity. This paper gives a brief account of sequential methodology that is a powerful but demanding approach to the conduct of clinical trials. Then a SAS application program (PEST 4) which supports sequential clinical trials will be described.	clinical trial, dataset, interim analysis		5
31	Software Validation in Clinical Trial Reporting: Experiences from the Biostatistics & Data Sciences Department	Andrea Baker	Data reported from clinical trials must meet the highest standards of quality and integrity and comply with strict regulations from the FDA and other worldwide regulatory agencies. The FDA's acceptance of data from clinical trials is based upon its ability to verify the quality and integrity of the data during its onsite inspections and audits. This includes onsite inspection of documentation that demonstrates the validation of software which has been developed in-house for clinical data reporting. At GlaxoSmithKline (GSK) we use SAS software as the primary tool for the analysis and reporting of clinical trial data. This presentation highlights the need for software validation and describes how validation processes can be applied to clinical trial reporting. The following topics will be included: Why Validate? What is Validation? What Validation isn't What Does Validation Involve? Implementing a Validation Process Conclusions/Considerations	data cleaning, clinical trial, quality control, clinical data, adverse events	presentation	5
32	SOS (Save Our Space) - Matters of Size	Matthew Pearce	Disk space is one of the most critical issues when handling large amounts of data. Large data means greater processing time, more resources and therefore more money. In SAS the key to all this is the data set. This paper will compare and contrast the various methods of minimising the physical size of a SAS data set on disk. Accessibility is an important element to be considered here, and this paper will demonstrate that shear physical size is not the only consideration. There is little point in compressing a dataset to one tenth it's size if it takes ten times as long to read. Alternative techniques present within host operating systems will be analysed in addition to the more traditional SAS methods of data set reduction. Attention will also be given to some common sense coding methods of economising on size for existing data sets	dataset, attrib statement, cpu time		15
33	Speeding Up the Validation Process of Clinical Trials Data	Ali Dootson	Presentation	data cleaning, sas programming, excel, biostatistics, clinical trial, data governance, if-then-else		23
34	Statistics Courses - and How to Survive (Writing) Them	Paul Watson	Presentation			15
35	Successful Web Enablement of a SAS Product	Ian J. Sutton	This paper discuses the trials, tribulations and rewards of the conversion of our SAS OLAP Product (Futrix) to fully enable its functionality via the web. Various topics are discussed including what web technologies/languages we found most appropriate and the relevant enhancements that SAS V8 brings. We discuss the research we carried out and the amount of work that was involved, how to maximize your existing skills and investment in development, and the problems we encountered and how we solved them or worked around them. Also included is a demonstration of the final result: the web enabled Futrix product and what was achieved with approximately 1000 hours work	business intelligence, traffic data		6
36	Successful Web Mining at a Belgian Bank	Bart Dessent	Presentation	output delivery system, %if-%then-%else		48
37	The R in CRM Stands for Risk and Respect from Customers, not Relationships	Huw Davis	Presentation	product profitability		31
38	The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process	Matthew Glasson, Justine Eastman	Presentation	data mining, regression analysis, outlier, dataset, feature selection, oracle, score code		17
39	The Version 8 Applied Statistician	David Shannon	Version 8 of the SAS System has provided statisticians with several new features and tools that not only increase the availability of statistical methods, but also decrease the level of output manipulation and therefore time, required for reporting. This paper will demonstrate some of the new summary and graphical features available in Base SAS procedures, new features in commonly used `SAS/STAT` procedures and introduces new procedures such as boxplot, mi, and mianalyze. By using `ODS` objects the statistician can save time and code extracting statistical results in preparation for reporting. These features will be demonstrated, showing how to extract just the information you wish to report into data sets or directly to an output file. Furthermore this paper will consider how to control output layout and style to represent ICH (International Conference on Harmonisation) guidelines	proc step, proc means, proc glm, output delivery system, sample, proc univariate, proc genmod, regression analysis, random sampling, sas base, box plot, missing value, ods output, proc logistic, proc mi, class variable, exact test, sample size, imputation, confidence interval, logistic distribution, proc mixed		15
40	To ODS RTF and Beyond	David Shannon	The ability to send output to Microsoft Word was the most commonly requested function during the development of the Output Delivery System. Since version 8.1 `ODS RTF` has been formally available. The Rich Text Format (RTF) specification is a method of encoding formatted text and graphics which is read by Microsoft Word and several other text editors. So now that we have the ability to send output to Word, how can we apply it? What are the advantages over traditional fixed space output? How can we go beyond the documentation to extract some of Microsoft Word's features? This paper will address these questions demonstrating how to define and apply generic appearance to a project and consider the advantages of RTF output to both the programmer and end user. Furthermore it will be shown how to go beyond the documentation by embedding RTF codes to enhance your reports. Finally this paper addresses some practical considerations when generating and distributing RTF files	output delivery system, proc step, ods rtf, proc report		12
41	Understanding Macros	Bob Newman	Presentation: I like macros. But sometimes they can be hard to understand. Part of the problem, I think, is that you have to think in two languages at once. You're using the macro language to generate some code in another language - SAS code, or SCL, or maybe display manager commands. If something goes wrong, you don't immediately know whether the problem is with the code itself, or with the macro that was generating it. It doesn't help when there are similar constructs - if/then/else, "do" loops and so on - in both the languages involved. Long strings of ampersands can also be - let's be honest - a bit intimidating. The idea of this paper is to eliminate these feelings of confusion and fright by forgetting (as far as possible) about SAS and SCL code, and looking only at the macro language. The downside of this is that all the macros here will be guaranteed utterly useless.	macro variable, macro put, macro quoting function, macro function, macro definition, %if-%then-%else		10
42	Visualisation in SAS	Ian Sedgwick	Presentation	bar chart, standard deviation, proc freq, bubble plot, contour plot, data mining, ods pdf		28
43	Your Clinical Trials Data Entry and Management Solution - The SAS UK Clinical Data Management Knowledge Solution	Jane Powell	Presentation	clinical trial, clinical data, dataset, data cleaning, data governance, phase i, phase iv		19
44	Your Graphs and Tables at Their Best on the Web with ODS	LeRoy Bessler, Francesca Pierri	You can create and deploy informative and influencing graphs and tables for the web, and link them to each other, with `SAS/GRAPH` ,	proc step, proc template, output delivery system, proc print, bar chart		31

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