Elaboration

"Elaboration enables you to statistically control variables that may contribute to (elaborate on) the basic relationship identified in the initial data analysis" (Dane, 1990, p. 141)

Once you have completed the analysis of data, you may need to begin the process of exploring and interpreting relationships among variables. This process is called elaboration, and allows for the examination of possible reasons 'why' the data is showing what it is showing.

This involves cross checking other variables against the two primary variables identified as having a correlating relationship. These other variables could be viewed as 'alternative hypothesis', and how they impact on the two primary variables could lead to possible causal relationships.

For example, if a survey found a correlation between 'fluency in Te Reo Maori' and 'Urban Dwelling', you may wish to test this against age, level of income, and level of education. If these variables are tested against fluency in Te Reo and no change occurs across the data, then you can eliminate them as possible causes on the relationship between the two primary variables.

Elaboration is similar to a process of elimination whereby variables are tested one by one to see how they impact on observed relationships. Some methods that can be used during elaboration analysis are:

  • Pearons Product Moment Correlation Coefficient – This measures the tendency of two variables on the one object to increase or decrease together.
  • Multiple Regression – This is a technique used for the estimating of simultaneous correlations among any number of predictor variables and a single response variable.
  • Discriminant analysis – This is a technique used to estimate the relationship between predictor variables and catagorical responses.

When conducting exploratory analysis it is easy to make the mistake of making conclusions that have not been fully tested. These untested conclusions are called Ex post facto explanations. Be cautious in your research, and ensure that your analysis is thorough and clear. Steer clear from Ex post facto explanations.