Data Visualization

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Data Visualization
Sanjay Matange 0
Extended Bands

In the Clinical Research domain, there is often the need to display lab values by treatment or test and it is often useful to view this data along with reference lines showing the normal ranges.  The obvious way is to use reference lines to denote the normal ranges. SGPLOT Code: proc sgplot data=band; scatter x=x y=y

Data Visualization
Sanjay Matange 0
Butterfly plots

When comparing results by category and group,  putting the items to be compared close together usually leads to a graph that is easier to decode.  Take the case of the data (simulated) shown below. Here we have population by age group and sex.  To compare the population by sex, it is

Data Visualization
Sanjay Matange 0
Spark lines made easy

Spark lines, made popular by Edward Tufte, provide a way to visualize trends in a concise space, often inline with the rest of the narrative or data. Previously, I posted an article on Spark Plots in which I created different plot types, some of which included multiple graphs and data in each row.  For such

Advanced Analytics | Data Visualization | Programming Tips
Angela Hall 0
And the difference between Business Intelligence and Business Analytics is ...

After some discussion with SAS Product Marketing yesterday, we devised this response to everyone's question about the Business Analytic differentiator that SAS provides. ********************************************************************************************************* Business Intelligence is one of the key components from SAS that ties into a suite of analytic techniques, information handling and performance infrastructures needed to deliver

Data Visualization
Sanjay Matange 0
LFT Panels

CTSPedia.org is a website of Knowledge Base for Clinical and Translational Research.  On this site you can find sample graphs for statistical analysis of safety data for Clinical Research.  Graphs included in this resource have been submitted by contributors, and include a graph for Liver Function for different tests by treatment.

Data Visualization
Sanjay Matange 0
Bar chart with response sort

A graph in a recent article in Fortune magazine caught my eye.  The graph shows the cost of hosting the Summer Olympics over the past eight events.  Here is what I termed the "Medal" graph. Now, practitioners of the art of Effective Graphics would likely find some shortcomings in the graph.  Clearly

Data Visualization
Sanjay Matange 0
Broken Y-Axis with SAS 9.2

In the previous post on Broken Y-Axis, I reviewed different ways to display data as a Bar Chart, where the response values for some categories are many orders of magnitude larger than the other values.  These tall bars force  the display of other values to be squeezed down thus making it harder to compare

Data Visualization
Sanjay Matange 0
Broken Y-Axis

Often we want to display data as a bar chart where a few observations have large values compared to the rest.  Comparison between the smaller values becomes hard as the small bars are squeezed by the tall bars.  Here is an example data, and a bar chart showing the data. The large values

Data Visualization
Sanjay Matange 0
PharmaSUG 2012 update

PharmaSUG 2012 conference drew to a close today, concluding two and a half days packed with papers, presentations, posters, hands-on demos and super demos by SAS staff.  While the weather outside was a bit chilly from time to time, the conference what hopping with many user papers on how to

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