Background:
These pages refer to a draft paper by Vernon Gayle and Paul Lambert which introduces Quasi-Variance methods to a sociological audience
Gayle, V and Lambert, PS (2006) Using Quasi-Variance to communicate sociological results from statistical models(long version). Stirling: University of Stirling, Working paper 2006-3 of the Researcher Development Initiative project 'Longitudinal Data Analysis for Social Science Researchers'.
Gayle, V. and Lambert, PS (2007) Using Quasi-Variance to communicate sociological results from statistical models, Sociology, 41(6), 1191-1206.
'Quasi-Variances' are statistics associated with the parameter estimates of the different levels of categorical explanatory variables within regression format statistical models. The paper recommends that researchers publishing regression model results should routinely seek to present appropriate Quasi-Variance statistics, since these enable readers of these outputs to readily perform tests of difference between any combination of categorical factor parameter estimates (not otherwise possible without access to the full variance-covariance matrix for the estimates).
Quasi-Variance methods were introduced by David Firth. He has produced an online web-calculator which can be used by reseachers who produce models, in order to generate appropriate Quasi-Variance statistics.
When Quasi-Variance statistics have been generated, they would ordinarily be used in three ways:
- They may be reported next to the appropriate parameter estimates in a regression model output
- They may be used to undertake Wald-tests for the significance of the difference between any two categories of the categorical variable : this may be achieved by entering the unstandardised parameter coefficient and quasi-variance into this MS-Excel calculator
- They may be used to construct approximate confidence intervals for the differences between all categories of the categorical variable : these may also be generated by entering the unstandardised parameter coefficient and quasi-variance into this MS-Excel calculator
AN EXAMPLE (Figure 1 in the paper):
