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Resources for IDI users

This page contains resources for users of the Integrated Data Infrastructure (IDI).  

Collaboration spaces

MeetaData

MeetaData is an online collaboration space created by Stats NZ for all microdata users. MeetaData allows you to connect with other users, share knowledge, ask questions, share code, and talk about anything related to microdata.

If you are interested in becoming a member, email meetadata@stats.govt.nz

Technical forums

We invite researchers to share their IDI experience with others via forums and other seminars.

To be notified about upcoming forums, sign up for the IDI users mail group by emailing access2microdata@stats.govt.nz.

Technical resources

Search for indicators in the IDI

If you are scoping an IDI project, the Social Investment Unit’s (SIU) Social Investment Measurement Map (SIMM) can help you find out about what measures are available in the IDI. The SIMM provides searchable information about many of the IDI indicators, in particular those with a social investment focus. You can search by topic or agency, or search for keywords in descriptions. The SIMM will tell you if this information is available in the IDI, what type of measures are available for each indicator, and how often the indicator is refreshed. The SIMM is not an exhaustive list of IDI variables – SIU will continue to improve the SIMM and expand coverage.

Analytical layers

The SIU’s Social Investment Analytical Layer (SIAL) can be used to reformat the social sector data in the IDI into a series of event-structured tables. The tables produced have a consistent format, making the data easier and faster for IDI users to use and understand.

Visit GitHub to view or download the code needed to build the SIAL tables.

To use the code:

Further information can be found in the README file, or on the SIAL webpage.

 Linking methodology

Coding

The IDI is a large SQL database therefore intermediate SQL coding skills are strongly recommended. Researchers can undertake analysis using different software packages. Most researchers code in SAS or SQL, while others prefer coding in R or Stata.

Code sharing is allowed and encouraged in the Data Lab environment. Code is shared via the IDI Wiki and can be output checked and shared on MeetaData.

Confidentialising output  

  • Microdata output guide describes the methods and rules that researchers must use for confidentialising output produced from Stats NZ’s microdata.

 Updated 7 June 2017

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