Date: Mon, 24 Jan 2011 07:46:49 -0700
Reply-To: Jon K Peck <peck@us.ibm.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Jon K Peck <peck@us.ibm.com>
Subject: Re: New column in heading in variable view 19.0
In-Reply-To: <1295878474386-3354685.post@n5.nabble.com>
Content-Type: multipart/alternative;
Roles are set by the user. Currently, these simply make initial settings
in some dialog boxes. But if the roles are set correctly, it becomes
possible to automate and raise the level of abstraction of repetitive
tasks. For example, you might need to produce a standard set of
analyses/reports across a variety of datasets that may have a similar
structure but vary in the exact variables they contain or other details.
By abstracting the logic of a job to use roles, measurement levels, custom
attributes and other properties, you can reduce the number of versions of
a job that need to be developed and maintained.
I have seen customer sites where there are huge numbers of job files -
syntax, templates, macros, scripts, etc - that are very similar but
duplicated and modified, because the variables coming in are a little
different or the coding of variables is a little different. Once you
build a big set of jobs like this, making improvements or bug fixes
becomes a nightmare.
The long standing macro facility provides some possibilities for
abstraction, but it is static and can't use the metadata available in a
dataset. In contrast, the SPSSINC SELECT VARIABLES command allows you to
define sets of variables based on the metadata rather than just a list of
names. It can use explicit names, patterns in names, measurement level,
type (numeric vs string), custom attributes, and, finally, role, to define
sets of variables that can be used in the job. Of course, you could write
your own code to use this sort of information, but SELECT VARIABLES can do
a lot of this without the need to learn programmability.
So, suppose you have a standard questionnaire that is used in many
studies, but it has a few custom questions that vary from study to study.
You need to produce tabulations and estimate similar models for these
studies. By intelligent use of the metadata, including role, you can
perhaps have one master job rather than dozens. This leaves the analyst
or researcher free to focus on the brainwork part of the job rather than
the tedious mechanical and error prone parts.
In summary, it's all about generalization and automation. Role is just
one more attribute that can be used in this effort.
SPSSINC SELECT VARIABLES can be obtained from the SPSS Community at
www.ibm.com/developerworks/spssdevcentral and requires the Python
Programmability plugin/essentials.
Regards,
Jon Peck
Senior Software Engineer, IBM
peck@us.ibm.com
312-651-3435
From: Bruce Weaver <bruce.weaver@hotmail.com>
To: SPSSX-L@LISTSERV.UGA.EDU
Date: 01/24/2011 07:19 AM
Subject: Re: [SPSSX-L] New column in heading in variable view 19.0
Sent by: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
Oh dear...I just had a horrible vision of something like the Microsoft
Paper-Clip popping up, saying, "So...I see you want to run a regression
model!" :-O
Jon K Peck wrote:
>
> Role is a new attribute that can be used in some recent procedures to
> select variables into appropriate slots automatically in order to save
the
> user time. Its usage is similar to the way Role is used in SPSS
Modeler,
> but it is only used in a few procedures. There is a preference item in
> Edit>Options>General on whether to use this or not. You can see it in
> Data>Prepare Data for Modeling, which is in the Data Preparation Option
> and in Analyze>Regression>Automatic Linear Modeling.
>
> HTH,
> Jon Peck
>
>
>
>
>
> Jon Peck
> Senior Software Engineer, IBM
> peck@us.ibm.com
> 312-651-3435
>
>
>
> From: Martin Sherman <MSherman@loyola.edu>
> To: SPSSX-L@LISTSERV.UGA.EDU
> Date: 01/23/2011 06:27 PM
> Subject: [SPSSX-L] New column in heading in variable view 19.0
> Sent by: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
>
>
>
> Dear list: Upon looking at the data editor under variable view (with IMB
> SPSS Statistics 19.0) I noticed a new column headed with ROLE with the
> following options available
> input
> target
> both
> none
> partition
> split
>
> I have been unsuccessful in figuring out what these options refer to.
Does
> anyone have a clue? Thanks, martin sherman
>
>
-----
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/
"When all else fails, RTFM."
NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.
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