Research notes

Intergenerational Analyses using the IDI

Irene Wu 2017 (Statistics Summer Scholar) 

Insights from the Social Attitudes Survey New Zealand 2015

Clark Tipene 2016 (Sociology Summer Scholar)

Analysing social network data from the New Zealand General Social Survey 2014

David Chan 2016 (Statistics Summer Scholar)

Obtaining best estimates for Māori transitions through the life-course

Lucy Cowie 2015 (Psychology Summer Scholar)

Developing bias weights for the New Zealand Longitudinal Census

 Rahul Singhal 2015 (Statistics Summer Scholar)

Construction of life-course variables for the New Zealand Longitudinal Census

Chris Liu 2015 (Statistics Summer Scholar)

Investigating linkage bias in the New Zealand Longitudinal Census

Vera Clarkson 2014 (Statistics Summer Scholar)

An investigation of the statistical modelling approaches for the modelling the early life course project

Review of material examining influences on life-course

Dr Barry Milne 2012

This document contains details of studies conducted under the domains of health, education, social/justice which are relevant to the study of factors influencing the life-course. For each of the domains a subset of more detailed issues is listed, along with a summary which details the direction of the effect, a link to the appropriate reference(s) and a brief comment on the sample referred to in the reference.

Improving efficiency and underpinning transparency in research: enhancing research resources via a research repository

Emma Gullery 2012

Hospital discharge data has been widely used to study and estimate health care delivery as it changes through the years. Research into this field allows for policy development and analysis useful for both the consumer and provider. The National Minimum Data Set (NMDS) is a large data set containing information on hospital events that have occurred at every public and private hospital in New Zealand. The Enhancing Hospital Outcomes (EcHO) project was designed to analyse the quality of patient care in New Zealand using indicators to measure a variety of health conditions and events. Before developing methods to approach this task, care needed to be taken in applying analyses to the NMDS, given that the data collection spanned years of changing coding practices and the creation of new diagnostic categories. These changes highlight the need for data filtering. The Ministry of Health (MoH) has reported their filtering techniques of the NMDS and code was developed to replicate the process to enable more accurate estimates.

Through close inspection of the related MoH filtering publications, inconsistencies were found in their figures raising doubt when trying to reproduce the computer code. Despite this, figures were compared and for most categories filtering exclusions numbers from the EcHO project were similar to those released by the MoH. Categories that were found to produce dissimilar results to the MoH figures were error diagnosis-related groups (DRGs), endoscopic retrograde cholangio pancreatography (ERCPs), inconsistent stays, mental health cases and disability support services cases (DSS).

Allowing public access to these developed methods of filtering and healthcare quality indicators was a main objective to the project. Hypertext Markup Language, or HTML, code was written to publish the SAS code for the EcHO project on the website belonging to the New Zealand Social Sciences Data Service.