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"entertaining and informative"

Organon

Feb
01

Standard Programs vs. Standard Macros

  • Katja Glass
  • 01/Feb/2012 08:00
Personally I cannot understand discussions about creating standard programs or standard macros. I could only imagine very rare situations where standard programs will make more sense than standard macros.
Jan
01

2012 A Survival Guide

  • George Lazlo
  • 01/Jan/2012 01:00
Happy New Year to you. I am saying ‘to you’ deliberately since I’d like this post to be read as if we were good friends having a chat in a cafe over a cup of coffee. I realize though that by the time you finish reading this you may not want to be my friend. Let’s see what happens.
Dec
15

Validation, easy as pie

  • Daniel Boisvert
  • 15/Dec/2011 07:53
Keep reading! Validation really isn’t that bad. Ok, that’s the last time I’m mentioning the V word. I know whenever I bring it up you cringe a little. Stay with me. Validation is as easy as baking a pie (Oh, sorry I said it again).
Dec
01

Future programmers – assuming they can program already

  • Shafi
  • 01/Dec/2011 06:01
Trainees of today will be the programmers of the future, but is there too much of one global community and not enough of local level support to ensure we have local programmers in the future?
Nov
15

The “Standard” Deviation: When is it OK to Stray?

  • Joanna Koft
  • 15/Nov/2011 08:00
At this stage in the game, I think we, as sponsors, have finally moved from “if we have to implement standards” to “how we should be implementing standards”. As it turns out, I think we can all agree that the latter is much more challenging. Standards such as CDASH, SDTM and ADaM are available for our implementation pleasure….along with a new set of challenges. Sponsors must take the data models and implementation guides and apply/integrate them into their own processes. Sounds easy enough, no?
Nov
01

Statistical Programming more than just SDTMs and ADaMs

  • Greg Fagan
  • 01/Nov/2011 14:33
I am a Statistical Programmer, here me roar! That statement sounds very bold and confident; however, to be honest, I am not sure what a Statistical Programmer does anymore. This post may be rehashing some previous topics about specializing or not – but I will try not to be redundant. I want to speak about Statistical Programming – proper.
Oct
01

Specifications - less is more but not enough

  • Katja Glass
  • 01/Oct/2011 07:10
Specifications are everywhere. Datasets are specified, reports are specified, systems are specified and we all have to deal with the specifications. Often enough we have to create them on our own. But how to make good specifications? Less is more, but is it still enough? What level of detail will fit our requirements?
Sep
15

Open vs. Proprietary Software: Value and Risk

  • Max Kaevsky
  • 15/Sep/2011 07:01
In his recent blog, Dave Handelsman looked at open source vs. proprietary software debate and concluded that businesses should evaluate software not based on “free vs. fee” but instead on “value vs. risk”. I completely agree with Dave’s assessment. I would go a step further and conclude that open source software provides better value with less risk than proprietary software. Let’s take a closer look.
Sep
01

Open vs. Proprietary Software: What’s my best bet?

  • Dave Handelsman
  • 01/Sep/2011 07:09
Free vs. Fee??
Aug
15

What Model Are You? Exploring the different working structures that exist to support SDTM development

  • Joanna Koft
  • 15/Aug/2011 08:00
As our industry standard of regulatory submissions shifts towards CDISC-compliance, sponsors must adopt new processes to support the shift. With the implementation of the submission standards of SDTM, ADaM, and Define.xml, this adds up to a plethora of new processes and responsibilities. SDTM alone encompasses many of these new processes….including new tasks such as SDTM annotation of CRFs, creation of SDTM metadata specifications, programming of SDTM datasets and parallel programming/QC of SDTM datasets. This puts additional pressures on groups such as statistical programming to be able to efficiently get their work done while adhering to new data standards.
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