SCSUG 2016 Papers - Index

39 papers. Source: SCSUG (South-Central SAS Users Group) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Extras	Pages
1	%EventChart: A Macro to Visualize Data with Multiple Timed Events	Andrew Peng	An event chart is a tool to visualize timeline data with multiple events. A typical event chart plots one horizontal line for each subject, with the x-axis as time intervals from a base event and the y-axis as the subject ID. Markers with different attributes are put on the line for different types of events. This paper introduces a SAS macro, %EventChart, which is capable of producing event charts with several user-friendly options. In the macro, the `SGPLOT` procedure is utilized to produce the plot and the macro takes advantage of the STYLEATTRS statement, which is newly available in SAS 9.4, to specify colors and markers for different categories. This paper discusses the data structure of the input file, followed by an in-depth description of required and optional arguments. An application of the macro to an oncology study is provided	proc sgplot, clinical trial, unique key, proc step, sample, macro quoting function	source	6
2	An Ad Hoc Method for Computing Pseudo Effect Size for Mixed Models	Kathryn G. Tippey, Michael T. Longnecker	Effect size is increasingly being reported in journals across multiple domains. Many fields that use complex experimental designs, such as psychology and engineering, must analyze those designs using mixed models. Because of the intrinsic nature of mixed model computations, none of the packages (R, SPSS, SAS, STATA, etc.) provide effect sizes. Hence, when analyzing models that use fixed and random factors, such as split-plot and repeated measures designs, an alternative method must be used to compute effect size using output from procedures capable of appropriately analyzing mixed models. This paper presents an ad hoc method of computing effect size by working backwards from the F-values output by SAS `PROC MIXED` to produce eta-squared, omega-squared, and partial eta-squared pseudo estimates. A SAS Macro will be provided to perform the calculations. Keywords: Effect Size, Mixed Model	effect size, proc mixed, proc step, covariance, covariance structure, proc glm, proc genmod, anova	source	7
3	Analysis of degradation patterns in the clinical efficacies of anti-microbial drug usage	Shweta Arya, Bhuvaneswari Yallabandi	In this paper we are analyzing the healthcare industry and primarily the anti-microbial drugs used to cure Urinary Tract infection and other diseases. We have provided analysis on how usage of drugs differ with different sexes and with different age groups. We also analyze how much amount is being spent on individual drugs and how many doses were sold. Additionally, we are predicting and identifying what factors lead to a patient to get re-admitted to a healthcare provider after getting diagnosed once. We are leveraging power of SAS with models such as Decision Trees, Regression and Neural Network to identify the aforementioned factors. Finally we are also forecasting the price of such drugs using SAS Forecasting tool and identifying if a patient can opt for any inexpensive substitute generic drug instead of spending a fortune on its expensive counterpart	proc hpsplit, data cleaning, regression analysis, neural network, roc curve	source	12
4	Analyzing sentiments in tweets for Tesla Model 3	Praneth Guggilla, Tejaswi Jha, Goutam Chakraborty	Tesla Model 3 is making news in the history of automobiles as never seen before. The new electric car already has more than 400,000 reservations and counting. We carried out a descriptive analysis of sales of all Tesla models and found that the number of reservations till date are more than three times sales of all previous Tesla cars combined. Clearly there is a lot of buzz surrounding this and such buzz influences consumers' opinions and sentiments and which in turn lead to bookings. This paper aims to summarize findings about people's opinions, reviews and sentiments about Tesla's new car Model 3 using textual analysis of tweets. For this, we used the live streaming data from Twitter over time and studied its pattern based on the booking timeline. We have been collecting data from March 2016 when the interest of people in this model spiked suddenly. A sample of 1000 tweets was analyzed from a total of about 10,000 collec ted via fumes	data mining, proc freq, sample, parsing, data cleaning	source	12
5	Anatomy of a Merge Gone Wrong	Joshua M. Horstman	The merge is one of the SAS programmer's most commonly used tools. However, it can be fraught with pitfalls to the unwary user. In this paper, we look under the hood of the `DATA STEP` and examine how the program data vector works. We see what's really happening when datasets are merged and how to avoid subtle problems	merge statement, pdv, by group processing, out=	source	5
6	Beyond IF THEN ELSE: Techniques for Conditional Execution of SAS Code	Joshua M. Horstman	Nearly every SAS program includes logic that causes certain code to be executed only when specific conditions are met. This is commonly done using the IF…THEN…ELSE syntax. In this paper, we will explore various ways to construct conditional SAS logic, including some that may provide advantages over the IF statement. Topics will include the SELECT statement, the `IFC` and `IFN` functions, the CHOOSE and WHICH families of functions, as well as some more esoteric methods. We'll also make sure we understand the difference between a regular IF and the %IF macro statement	if-then-else, ifn, select, macro definition, sas programmer, subsetting if, whichn, %if-%then-%else, missing value, proc format, ifc, when, proc step	source	6
7	Bringing the US Department of Defense from PC to the Enterprise!	Erin Stevens	Presentation	analytics platform, inventory optimization, sas grid, sas base, grid computing, in-database processing, cpu time	source	14
8	Building a Better Dashboard Using SAS Base Software	Kirk Paul Lafler, Joshua M. Horstman, Roger D. Muller	Organizations around the world develop business intelligence dashboards, sometimes referred to as enterprise dashboards, to display the current status of "point-in-time" metrics and key performance indicators. Effectively designed dashboards extract real-time data from multiple sources for the purpose of highlighting important information, numbers, tables, statistics, metrics, performance scorecards and other essential content on a single screen. This presentation explores the basic rules for "good" dashboard design, the metrics frequently used in dashboards, and the use of best practice programming techniques in the design of highly interactive, filterable, and drill-down dashboards using Base-SAS software	proc step, bar chart, vertical bar chart, proc format, if-then-else, dataset, proc template, proc print, ods html, footnote statement, proc sgpanel, user-defined format, histogram	source	17
9	Categorization of Fitbit's Customer Complaints on Twitter	Sapna Bhoir, Jacky Arora	All companies are trying to be more customer-centric by implementing new measures to enhance the consumer experience. One such measure recently implemented by many companies is "Social Media Customer Service". According to J.D. Power, 67% of consumers have used a company's social media support page for customer service issue.[5] It has been reported that consumers can expect a reply within a couple of minutes from the support team regarding the severity of the issue. Fitbit is one such company, which has grown quite popular in the recent days. It has encouraged its customers to generate a buzz in social media by expressing their reviews, discussing the new product launch and utility of Fitbit in customer's day-to-day life. However, on the flip side, Fitbit's Twitter support page is flooded with issues that consumers are facing while using their products. There is at least one tweet (@FitbitSupport) every minute by a user or by the support team responding to a user's complaint	parsing, dataset, data cleaning	source	17
10	Contextualized Market Basket Analysis - How to learn more from your Point of Sale Data in Base SAS and SAS Enterprise Miner	Andrew A. Kramer	Recent advances in unsupervised learning have led both academics and private-sector data science teams to scan consumer market basket data, looking to create advanced predictive models such as recommender systems . However, these new statistical techniques fail to address the fundamental questions that a Market Basket Analysis (MBA) presents for any retailer: do these associations create profitable, long -term relationships with my valued customers? This paper will address how Macro Variab les, `PROC SQL` and Database steps can be used understand the profit implications of any retailer's Market Basket Analysis	data mining, proc sql, market basket analysis, proc step, do loop, proc means, sas base, macro variable		11
11	Custom Excel Toolbox	Michael McCarthy	Data users frequently have a need to merge Microsoft `EXCEL` data with other data sets. While the TASK tab within the SAS Add-In 7.12 for Microsoft Office ribbon offers access to a variety SAS analytics, it doesn't provide an option to join or merge user selected cells. This paper is written for BASE SAS programmers who want to use the SAS Add-In 7.12 for Microsoft Office to perform a "`PROC SQL` JOIN" on user selected Microsoft `EXCEL` data, without leaving the `EXCEL` environment	excel, sas base, dataset, proc sql, call execute, create table, proc step, macro definition, macro variable, character functions, char., data step		10
12	Determining the functionality of Water Pumps in Tanzania Using SAS EM and VA	Indra Kiran Chowdavarapu, Vivek Damodaran Manikandan	Accessibility to clean and hygienic drinking Water is a basic luxury every human being deserves. In Tanzania, there are 23 million people who do not h ave access to safe Water and are forced t o walk miles in order to fetch Water for daily needs. The prevailing problem is more of a result of poor maintenance and inefficient functioning of e xisting infrastructure such as Hand Pumps. To solve the current Water crisis and ensure accessibility to safe Water, there is a need to locate non- functional and functional Pumps that need repair so that they can be repaired or replaced. However, it is highly cost ineffective and impractical to manually inspect the functionality of each Water Pump. The objective of this study is to build a model to predict which Pumps are functional, which needs some repair and which don't work at all	proc hpsplit, proc hpforest, data cleaning, data mining, confusion matrix, nominal variable, feature selection, training set	source	9
13	Differentiate Yourself	Kirk Paul Lafler	Today's employment and business marketplace is highly competitive. As a result, it is necessary for SAS professionals to differentiate themselves from the competition. Success depends on a number of factors, including positioning yourself with the necessary technical skills in relation to the competition. This presentation illustrates how SAS professionals can acquire a wealth of knowledge and enhance their skills by accessing valuable and free web content related to SAS. With the aid of a web browser and an Internet connection, anyone can access published PDF papers, Microsoft Word documents, Microsoft PowerPoint presentations, student notes, instructor lesson plans, hands-on exercises, webinars, audios, videos, a comprehensive technical support website maintained by SAS, and more to acquire the essential expertise that is needed to cut through all the marketplace noise and begin differentiating yourself to secure desirable opportunities with employers and clients	sas programmer, sas consultant	source	20
14	Downloading, Configuring, and Using the Free SAS University Edition Software	Ryan Paul Lafler, Kirk Paul Lafler, Charles E. Shipp	The announcement of SAS Institute's free "SAS University Edition" is an exciting development for SAS users and learners around the world! The software bundle includes Base SAS, `SAS/STAT`, `SAS/IML`, Designer Studio (user interface), and `SAS/ACCESS` for Windows, with all the popular features found in the licensed SAS versions. This is an incredible opportunity for users, statisticians, data analysts, scientists, programmers, students, and academics everywhere to use (and learn) for career opportunities and advancement. Capabilities include data manipulation, data management, comprehensive programming language, powerful analytics, high quality graphics, world-renowned statistical analysis capabilities, and many other exciting features. This paper presents the process of downloading and configuring the SAS University Edition	sas studio, proc step, sas base, data governance, proc sql, excel	source	15
15	Effective method on curing heart disease	K. Varadarajan, Surya Bhaskar Ayyalasomayajula		time series analysis, regression analysis, moving average, stepwise selection	source	12
16	Enabling news trading by automatic categorisation of news articles	Praveen Kumar Kotekal, Vishwanath Kolar Bhaskara	Traders making decisions based on news developments is nothing new. Any big market announcement of a company such as annual and quarterly earnings, dividend announcements, acquisitions, mergers, tender offers, stock splits or major management changes are known to have direct impact on the company's stock prices and news traders have always evinced keen interest to exploit and act on this information. However, in an age where news is novel only for few minutes it is important for traders to identify its underlying message, assess its possible impact on stock trends and take on the spot decisions before the market has had time to adjust itself to this news. Through this project we predicted the direction of stock price changes immediately after the news article publication and also major factors that influence either rise or fa ll of stock prices	data mining, parsing	source	9
17	Fast Dashboards: Producing real-time dashboards using SAS Event Stream Processing.	D. Rierson	Fast is a relative term. In the connected, always-on, real-time world computers can continuously send information much faster than humans can understand, categorize or visualize it. Much of what we use computers for is to slow down that information data stream in order to aggregate, transform, analyze and store it for use at a future time and date. Event stream processing is a technology used to help with this task. It is an incredibly fast, in-memory based technology designed to examine streaming data at machine time speeds: hundred, thousands and millions of events per second. At the same time, this technology puts that data steam into a better, understandable context for ultimate consumption by humans.	stream processing, real-time processing, rest api	source	19
18	Good Programming Practice when Working Across PC SAS and Unix SAS	James Zhao	This paper examines good programming practices to address common issues across PC SAS and UNIX SAS. They include: 1, Define forward or back slash for file paths in `LIBNAME`, `FILENAME`, and `%INCLUDE` statements consistently or dynamically; 2, Avoid the use of mixed case for file path and dataset names; 3, Avoid the use of X commands in SAS code to execute statements on the operating system which only works on Windows but not on UNIX; 4. Use appropriate SAS rounding function for numeric variables to avoid different results when dealing with 64 bit operating systems and 32 bit systems; 5, Use SAS Enterprise Guide to access and run PC SAS programs in UNIX efficiently	sas enterprise guide, numeric variable, numeric functions	source	5
19	Highly Customized Graphs Using ODS Graphics (SAS)	Warren F. Kuhfeld	Y ou can use annotation, modify templates, and change dynamic variables to customize graphs in SAS. Standard graph customization methods include template modification (which most people use to modify graphs that analytical procedures produce) and SG annotation (which most people use to modify graphs that procedures such as `PROC SGPLOT` produce). However, you can also use SG annotation to modify graphs that analytical procedures produce. Y ou begin by using an analytical procedure, `ODS` Graphics, and the `ODS` OUTPUT statement to capture the data that go into the graph. Y ou use the `ODS` document to capture the values that the procedure sets for the dynamic variables, which control many of the details of how the graph is created. Y ou can modify the values of the dynamic variables, and you can modify graph and style templates	sg annotation, proc step, if-then-else, macro definition	source	21
20	How to stop Stephen Curry	Wei Gao, Vrushali Walde	Stephen Curry is a professional basketball player for the Golden State Warriors of the National Basketball Association (NBA). With 30.2 points per game for the 2015 -2016 season, he is the top NBA 3-point shooter and seems to be an unstoppable player in NBA. He led the Golden State Warriors to an astonishing 73 win and 9 lose record for 2015-2016. So the focus of this research is how to defend him. In the 2015-2016 season, among the 73 winning games, his 3- point percentage is 46.6%. However, among the nine losing games, the 3-point percentage dropped to 35.4%	proc freq, response variable, regression analysis	source	11
21	Hybrid recommendation system to provide suggestions based on user reviews	Shanmugavel Gnanasekar, Ravi Shankar Subramanian	If you have ever shopped on Amazon, Pandora or Netflix, you would have probably experienced recommendation systems in action. These systems analyze the historical buying behavior of their customers and make real time recommendations to them. The back end of these systems contain data mining models that make predictions about the product relevant to you. We plan to build a similar recommender system to suggest restaurants to user. All recommender system in market suffer from inaccuracy. We intend to combine content from Yelp reviews with user's profile, restaurant profile to improve the accuracy of the recommender system. To implement our idea, we downloaded 2.2M reviews and 591K tips by 552,000 users from the Yelp website. The dataset for 77,000 restaurants contain information such as user profile information. Traditional systems utilize only user's ratings to recommend new restaurants	recommendation engine, proc sql, macro loop, create table, proc step, macro definition, data mining	source	10
22	Key Reasons for SAS Data Set Size Difference by SAS Grid Migration	Piyush K. Singh, Prasoon Sangwan	When SAS users move from traditional departmental server to Grid environment they face many challenges with new SAS Grid Platform settings. This paper describes one of such issue as "SAS Data Set Size" difference from non-Grid SAS server to SAS Grid Platform. This paper explains few key reasons like SAS Encoding, 32bit vs 64 bit SAS, BUFSIZE, Database Encoding etc. which affect the data set size during executing SAS job to SAS Grid Platform. It explains how these factors impact the data size and how we can address these issues to match to original size of SAS data sets. This will help users and SAS administrators to adopt new SAS Grid platform easily and in efficient manner	sas grid, data step, length statement, sas log, sas enterprise guide, proc step, sas output, options statement, libname statement, sas administrator	source	10
23	Let the CAT Out of the Bag: String Concatenation in SAS 9	Joshua M. Horstman	Are you still using TRIM, LEFT, and vertical bar operators to concatenate strings? It's time to modernize and streamline that clumsy code by using the string concatenation functions introduced in SAS 9. This paper is an overview of the CAT, CATS, CATT, and CATX functions introduced in SAS 9, and the new CATQ function added in SAS 9.2. In addition to making your code more compact and readable, this family of functions also offers some new tricks for accomplishing previously cumbersome tasks	character functions, sas 9, catq, ifc, sas programmer	source	7
24	Optimization of Refining Crude Distillation Process Unit using Process Simulation and Statistical Modeling Methods	Jose Bird	In this paper we implemented a methodology to optimize the operation of a refining crude distillation unit using a combination of process simulation and statistical modeling methods. The primary objective was to estimate a set of operating targets for col umn pumparound and bottoms stripping steam flows that maximize the unit profitability over a typical range of crude rate and crude quality operating conditions. The crude unit has an advanced process control application that maximizes product draw rates bu t does not optimize the above variables. We used process simulation to evaluate the crude distillation unit performance over a feasible range of pumparound and bottoms stripping flows as existing operating data did not provide sufficient data. Crude quality and crude feed rate were sampled randomly from actual operating data to account for their inherent process variability	regression analysis, proc reg, multiple regression, scatter plot, proc step	source	18
25	Optimize the Domestic Air Traffic System of United States using SAS Enterprise Miner	G. Piyush, Anuj Dwivedi, Aditya Agrawal	A flight delay is one of the major concern for the Aviation industry in the United States. Out of 8 million domestic flights, about 25% get delayed, and 1.5% flights get canceled every year. Delays lead to excess cost resulting in billions of dollars in loss to the flight carriers and the entire aviation industry. At the same time, it restricts the a irline companies to deliver better services to the passengers. In today's data-driven world, with the availability of tonnes of on time flights data, the delays can be optimized. The first part of this paper analyzes the on -time performance data between the period of November 2015 to May 2016 collected from the open data center of US Bureau of Transport Statistics and the daily weather from the Weather Underground to estimate the significant factors responsible for the flight delays such as Weather delay, Carrier delay, National Airspace System(NAS) delay and Late Aircraft delay	data mining, mis	source	16
26	Parsing Useful Data Out of Unusual Formats Using SAS	Andrew T. Kuligowski	Most "Introduction to Programming" courses will include a section on reading external data; the first assumption they make will be that the data are stored in some sort of documented and consistent format. Fortunately, in the "real world", a lot of the data we deal with has the same basic assumption of occurring in a documented, consistent format - a lot of it, but not all of it. This presentation will address some techniques that can be used when we are not dealing with cleanly formatted data, when the data we want is in a less -than-ideal format, perhaps intermingled or seemingly buried with unnecessary clutter. It will discuss the principles of using SAS to parse a file to extract useful data from a normally unusable source. This will be acc omplished by citing examples of unusual data sources and the SAS Code used to parse it Keywords: INDEX Function, INPUT Statement, Parser	input statement, named input, proc print, proc step, conditional do loop, index, sas log, sample, sas base, character functions, cpu time, end	source	15
27	Point-and-Click Programming Using SAS Enterprise Guide	Ryan Paul Lafler, Kirk Paul Lafler, Mira Shapiro	SAS Enterprise Guide empowers organizations, programmers, business analysts, statisticians and end-users with all the capabilities that SAS has to offer. This presentation describes the built-in wizards to perform reporting and analytical tasks, access to multi-platform enterprise data sources, the delivery of data and results to a variety of mediums and outlets, data manipulation without the need to learn complex coding constructs, and support for data management and documentation requirements. Attendees see the graphical user interface (GUI) to access tab-delimited and `EXCEL` input files; subset and summarize data; join (or merge) two tables together; flexibly export results to HTML, PDF and `EXCEL`; and visually manage projects using flowcharts and diagrams	excel, sas enterprise guide, dataset, proc means, data governance, delimited file, sas output, proc sql	source	18
28	PRESTO! CHANGEO! Making Data Transformations Look Like Magic	Patricia Hettinger	If you need to do data transformations such as from numeric to character, character to numeric, etc., here is a discussion of some useful SAS functions. The paper will also discussion automation methods including table driven transformations	hash table, proc step, proc format, sas function, lookup, numeric variable, proc compare, permanent library, sas enterprise guide	source	13
29	Proc SQL Self-Join for Aggregation	Steve Fleming	Have you ever needed to aggregate data within a dataset up to a certain record? For example, you might count how many transactions an account has had prior to the current transaction. Using a `PROC SQL` self-join can accomplish this task. This approach will be compared to `DATA STEP` Hash code, and advantages and disadvantages of each approach will be discussed	proc sql, proc step, hash table, sample	source	6
30	SAS Enterprise Guide for LASR Server	Piyush K. Singh, Prasoon Sangwan	It would be very helpful for SAS Enterprise Guide users if they can upload the data to LASR server (SAS Visual Analytics) directly from process flow. To achieve this functionality user needs to be given proper metadata access to load the table. For broader user, it becomes easy to m anage the access, if we can use Access Control Template (ACT) in management console. ACT can be created with appropriate privileges and applied to the specific groups. This paper explains, how SAS Administrator can manage SAS Visual Analytics environment for their SAS Enterprise Guide users, so that they can load the data to LASR and can run SAS program. User can use SAS Enterprise Guide to create different kind of reports from LASR tables	sas enterprise guide, sas management console, libname statement, unstructured data, dataset, sas administrator	source	11
31	SASGSUB for Job Workflow and Log Files	Piyush K. Singh, Prasoon Sangwan	SAS Grid Manager Client Utility (SASGSUB) is one of the key clients for the users to use SAS Grid platform. SASGSUB is standard SAS Grid Client Utility which may not fulfill every use case/business need. This paper describes few techniques to enhance SASGSUB capabilities with the help of shell scripting to enhance the default functionality of SASGSUB. It explains how to achieve the business needs like creating Job workflows for example to execute SAS jobs after the completion of set of running jobs, copy SAS log files from GRIDWORK to specific location without deletion from defau lt location (deletion of GRIDWORK files lead to SASGSUB fail to check the job's status) etc	sas log, data cleaning, sas grid	source	9
32	Sentiment Analysis of Opinions about Self Driving Cars	Nachiket Kawitkar, Swapneel Deshpande, Goutam Chakraborty, Miriam McGaugh	"From 2020, you will become a complete backseat driver", says the Guardian. The manufacturers are claiming that the Self driving cars will revolutionize motoring. However, few wonder if the greatest danger for these cars is that they will be "too safe" to drive. While few automakers believe that newest technology and added features in these cars will potentially save 30,000 lives a year. The only obstacle to that is convincing the customer to give up the control of their car and hand it to a computer. Recently, Tesla made its cars semi-autonomous, not only did the newer version of their cars have an autopilot feature but also the tens of thousands of the existing customer cars became way better with an overnight update. However, the company recommended keeping hands at the wheel at certain times when this autopilot version would like the human to take control of the car. While recently, Uber will be allowing its customers to call for its newer self-driving car cabs from their mobile phones. This feat makes Uber only one of the very few companies who achieved this milestone in the car and ride sharing market. A lot is being said about these self-driving cars online. A lot of comments, concerns, statements, suggestions can be found online, few are positive, negative or even neutral. So making a complete analysis of how people are taking this new technology currently is indeed challenging.	parsing, proc freq	source	13
33	Show Me the Money! Text Analytics for Decision-Making in Government Spending	Tom Sabo	Understanding organizational trends in spending can help overseeing government agencies make appropriate modifications in spending to best serve the organization and the citizenry. However, given millions of line items for organizations annually, including free-form text, it is unrealistic for these overseeing agencies to succeed by using only a manual approach to this textual data. Using a publicly available data set, this paper explores how business users can apply text analytics using SAS Contextual Analysis to assess trends in spending for particular agencies, apply subject matter expertise to refine these trends into a taxonomy, and ultimately, categorize the spending for organizations in a flexible, user-friendly manner. SAS Visual Analytics enables dynamic exploration, including modeling results from SAS Visual Statistics, in order to assess areas of potentially extraneous spending, providing actionable information to the decision makers	unstructured data, correlation, sas enterprise guide, nominal variable, dataset, proc hpsplit, binary variable, data cleaning	source	13
34	Strategies and Techniques for Getting the Most from Your Antivirus Software for SAS Users	Ryan Paul Lafler, Kirk Paul Lafler	Malware, sometimes referred to as malicious software, represent software threats engineered to damage computer systems without the knowledge of the owner using the system. SAS users are increasingly becoming more prone to malware attacks and need to have strategies and a set of guidelines to help them get the most out of their antivirus software. This presentation highlights the many different types of computer threats, classification approaches, detection strategies, and removal methods. Attendees learn what malware is; the types of malware including viruses, Trojans, rootkits, zombies, worms, spyware, adware, scareware, spam email, and denial of service (DOS) attacks; password protection and management strategies; software to detect and protect computer systems; techniques for the removal of malicious software; and strategies and techniques for protecting your computer and data assets		source	9
35	Ten Tips for Simulating Data with SAS	Rick Wicklin	Data simulation is a fundamental tool for statistical programmers. SAS software provides many techniques for simulating data from a variety of statistical models. However, not all techniques are equally efficient. An efficient simulation can run in seconds, whereas an inefficient simulation might require days to run. This paper presents 10 techniques that enable you to write efficient simulations in SAS. Examples include how to simulate data from a complex distribution and how to use simulated data to approximate the sampling distribution of a statistic	sample, residual, predictor variable, proc step, regression analysis, probability distribution, proc iml, standard deviation	source	15
36	Time Saver for All: A Macro Toolbox	Philip Jou	SAS Macros are a useful tool to any SAS Programmer. A macro variable can be used to assign a value to a variable that can be called repeatedly. A SAS Macro Definition serves a similar purpose but is used to repeat a set of instructions. This handy toolbox contains SAS Macro Functions that will allow a user to check the existence of a variable, get the number of observations in a dataset, and truncate the values of a dataset to name a few. This toolbox is useful to any flavor of SAS Programmer in any profession	macro variable, macro function, macro definition, options statement, macro call, proc step, character variable, numeric variable, proc contents, macro facility, missing value, proc sql, macro loop	source	20
37	Using Fuzzy Logic to Match a Street Address	Michael McCarthy	Stored process users frequently need to search SAS data set with imprecise or "Fuzzy" criteria. A "Fuzzy" search requires logic that ranks and decides an outcome based upon a relative quality of a match to the submitted string. This paper is written for BASE SAS programmers who want to perform a "Fuzzy Logic" search against a string field in a BASE SAS data set. A method to search an existing data field against a string of words entered by a user is described, and a step-by-step example of a fuzzy street address search using BASE SAS within stored process is presented	sas base, dataset, array, proc sql, proc step	source	5
38	Using INFILE and INPUT Statements to Introduce External Data into the SAS System	Andrew T. Kuligowski	The SAS System has numerous capabilities to store, analyze, report, and present data. However, those features are useless unless that data is stored in, or can be accessed by, the SAS System. This presentation is designed to rev iew the INFILE and INPUT statements. It has been set up as a series of examples, each building on the other, rather than a mere recitation of the options as documented in the manual. These examples will include various data sources, including `DATALINES`, sequential files, and `CSV` files. GETTING STARTED - BASIC INFILE / INPUT with `DATALINES` In order to bring data from an external source into your SAS session, the user must provide the answers to a couple of simple questions: Where is the data, and what d oes it look like? The INFILE statement will define the data source and provide a few tidbits of information regarding its form, while the INPUT statement will define the format of the data to be processed	input statement, infile statement, excel, pointer control, proc print, proc step, filename statement, length statement, list input, variable, character variable, missing value, proc format, run, out=	source	18
39	What's Hot - Skills for SAS Professionals	Kirk Paul Lafler	As a new generation of SAS user emerges, current and prior generations of users have an extensive array of procedures, programming tools, approaches and techniques to choose from. This presentation identifies and explores the areas that are hot in the world of the professional SAS user. Topics include Enterprise Guide, `PROC SQL`, `PROC REPORT`, Output Delivery System (`ODS`), Macro Language, `DATA STEP` programming techniques such as arrays and hash objects, SAS University Edition software, technical support at support.sas.com, wiki-content on sasCommunity.org, published "white" papers on LexJansen.com, and other venues	sas 9, sas base	source	18

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