ISSR is a national leader in developing, managing and analysing complex longitudinal data for social policy and research.

In addition to primary data collection, ISSR has extensive experience linking and analysing already existing data. In this way, we can capitalise on existing data investments made by government and other stakeholders. We undertake benchmarking data collection and analysis to provide a valid framework for making comparisons over time and across populations. 

Our analyses range from basic descriptive statistics aimed at a general audience to more rigorous multivariate analyses, and include:

  • State-of-the-art analytical software for a rich and complex understanding of data
  • Use of complex multi-level, longitudinal and spatial data structures
  • Development of mathematical and statistical models, geographic visualisation or the integration of research design, data collection, and analysis
  • Access to scientific qualitative data analysis using a range of software
  • Management of clients data for future use, including preserving, documenting or preparing data for archiving.

The student engagement-performance link

ISSR has a successful research partnership with the NSW Centre for Education Statistics and Evaluation (CESE) to build a powerful data resource from which to develop a better understanding of student engagement in the state and in Australia more broadly.

Our research aims to understand the causal relationship between engagement and student outcomes. Establishing causality with observational data, such as administrative or survey data is challenging. Unlike in experimental designs, researchers cannot randomly assign subjects to comparison groups or manipulate experimental conditions before assessing outcomes.

ISSR is using a generalised latent variable modelling framework that includes multilevel, longitudinal and Structural Equation Models (SEM) as a core analytic strategy for this project. We are also employing some econometric approaches for this project and extending them to the SEM framework as required.

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