measurement error

Mixed mode surveys: where will be in 5 years from now?

Some colleagues in the United Kingdom have started a half-year initiative to discuss the possibilities of conducting web surveys among the general population. Their website can be found here  One aspect of their discussions focused on whether any web survey among the population should be complemented with another, secondary survey mode. This would for example enable those without Internet access to participate. Obviously, this means mixing survey modes.

Bayesian Structural Equation Modeling

In August, I organised a three-week summerschool with my colleagues in Utrecht on new features in MPLUS 7, the software we use to build Structural Equation Models. Video’s of all lectures can be found here. The latest issue of Psychological Methods contains background reading of Bayesian SEM, which is the main new feature of SEM. I find this fascinating stuff, and can think of hundreds of articles that could be written about replications of Maximum Likelihood based approaches.

Statistical modeling: SEM

Sorry for the long silence: have been caught up in work and other things that were always more pressing than writing blog posts. Perhaps it is also because I found it hard to write about statistical modeling. Statistical models are usually complex, and therefore it is difficult to write about them in an accessible way. Statistical models are everywhere; their goal is to summarize our world in such a way as to capture the essence, and leave out the irrelevant complexities.

mode effects

One of the most interesting issues in survey research is the mode effect. A mode effect can occur in mixed-mode surveys, where different questionnaire administration methods are combined. The reasons for mixing survey modes are multifold, but usually survey researchers mix modes to limit nonresponse, reach particular hard-to-reach types of respondents, or limit measurement error. It is more common today to mix modes than not mix them, for some good reasons: