Hello
I have done a literature review on the theoretical elements of construct X. Now I want to compare the theoretical elements with the concrete empirical operationalisation of the construct. For example: the literatrue review reveals that construct X is theoretically about a changing envrionment. Thus, a changing environment is one of the theoretical elements of construct X. Through the concrete operationalisation of the construct I would like to see what changing envrionment means - the operationalisation may be a fast or a slow or a moderate changing environmnment. So its basically about finding answers how the construct is measured.
My approach would be to check the survey questions to see the concrete operationalisation of the construct through the questions the authors ask. Or it may be also worth looking at the antecedents of construct X in the empirical studies.
What would you recommend me - how can I extract the concrete operationalisation of a construct in an empirical study?
Your assertions provide a good framework for investigating construct X. However, based on the same kind of thought work I'm going through with my dissertation... I'm going to assert you should first consider the assumptions surrounding construct X. I will first conduct an analysis of the literature of my construct x and its possible cross-discipline (!!) variants using text analytic software (QDA Miner, etc.). After confirming the narrative hung together, I plan of creating a series of dynamic system models that specify antecedent and modifying conditions as well as feedback loops. Once I'm able to specify a logical model, I plan on creating a series agent-based a series of simulations (with unique starting and moderating conditions) to further characterize and understand the logical model. Yes, there are a series of natural feedback loops between model formulation and testing. Once I'm sure of the constructs and their dynamics, then and only then, will I create a survey instrument to generate "live" data. One of my largest lessons learned is the need carefully understand the assumptions behind the Maths you're using... (structural equation modeling, factor analysis, etc) and their underlying assumptions (ex: linearity, etc). Be aware of these conditions/ limitations before you start using them. And if you're going to use them without necessarily meeting all of the assumptions - please, please -- specify why you continued to use them and the most probable effect is on your results. Yes, the approach I plan on using seems laborious. But, I've thought long and hard about it and believe it will yield rich as well as verifiable knowledge.
Short answer: I don't see an "easy" way to approach your original prompt. But. I'm always open to alternatives...
- Badges
- Science method
- Similar topics
- Mathematics
- Statistics
- Statistical Techniques
- Meta-Analysis