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Re: Difference between attribute and disaggregate option for category combos

 

Hi Lars,

 

Thanks that is what I did. 

A general question – Isn’t this a way to easily add targets for certain data elements with known denominators eg population by setting up a dataset with e.g. Yearly or Quarterly period and then capture the target values as dataset attributes rather than create a new data element for the target which makes analysis more tricky since you need to link the 2 data elements to each other somehow?

 

Regards,

 

Elmarie Claasen

Hisp logo

Project Manager

Health Information Systems Program

Tel:      041-367 1027

Cell:     082 374 2209

E-mail:  <mailto:elmarie@xxxxxxxx> elmarie@xxxxxxxx

Skype:  elmarie.claasen52 

 

 

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From: Lars Helge Øverland [mailto:larshelge@xxxxxxxxx] 
Sent: 13 October 2015 02:00 PM
To: Elmarie Claasen
Cc: DHIS 2 Developers list; DHIS 2 Users list
Subject: Re: [Dhis2-devs] Difference between attribute and disaggregate option for category combos

 

Hi Elmarie,

 

the data dimension type on category and category combo indicates whether you want to use these as disaggregation categories (linked to data elements) or attribute categories (linked to data sets). So attributes refers to data set categories.

 

If you would like to create a data set category (e.g. one category option for "preliminary" and one for "validated"), then you need to set these to "attribute". So:

 

Category combo: "Output type" - data dimension set to "attribute".

Category: "Output type" -  data dimension set to "attribute".

Category options: "Preliminary output" and "Validated output".

 

You can now assign the "Output type" category combo to your data set, and the data entry screen will allow you to choose between preliminary and validated before entering data.

 

regards,


Lars

 

 

 

On Tue, Oct 13, 2015 at 1:34 PM, Elmarie Claasen <elmarie@xxxxxxxx> wrote:

Hi all,

 

I need to set up a dhis2 instance in which we want to capture the data for specific month twice e.g. preliminary output and validated output. We don’t need those to be added together as usual in a data element category combination. 

 

I have been looking into dataset category combinations but that looks a lot similar in the manual to attributes. Would like clarity on the difference between using disaggregate or attribute when selecting data dimension on a catcombo. 

 

Any suggestions on alternatives would be welcome J

 

Regards,

 

Elmarie Claasen

Hisp logo

Project Manager

Health Information Systems Program

Tel:      041-367 1027

Cell:     082 374 2209

E-mail:  <mailto:elmarie@xxxxxxxx> elmarie@xxxxxxxx

Skype:  elmarie.claasen52 

 

 

This message and any attachments are subject to a disclaimer published at  <http://www.hisp.org/policies.html#comms_disclaimer> http://www.hisp.org/policies.html#comms_disclaimer .   Please read the disclaimer before opening any attachment or taking any other action in terms of this electronic transmission. 
If you cannot access the disclaimer, kindly send an email to  <mailto:disclaimer@xxxxxxxx> disclaimer@xxxxxxxx and a copy will be provided to you. By replying to this e-mail or opening any attachment you agree to be bound by the provisions of the disclaimer. 

 

 

This message and any attachments are subject to a disclaimer published at http://www.hisp.org/policies.html#comms_disclaimer.  Please read the disclaimer before opening any attachment or taking any other action in terms of this electronic transmission.  If you cannot access the disclaimer, kindly send an email to disclaimer@xxxxxxxx and a copy will be provided to you. By replying to this e-mail or opening any attachment you agree to be bound by the provisions of the disclaimer.


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-- 

Lars Helge Øverland

Lead developer, DHIS 2

University of Oslo

Skype: larshelgeoverland

http://www.dhis2.org <https://www.dhis2.org> 

 


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*This message and any attachments are subject to a disclaimer published at 
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<http://www.hisp.org/policies.html#comms_disclaimer>.  Please read the 
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terms of this electronic transmission.  If you cannot access the 
disclaimer, kindly send an email to disclaimer@xxxxxxxx 
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