There is a video of me outlining Question 3 on the beach here in Vancouver on our Facebook page:
Take a look and here are the key points in text for your consideration over the next two weeks:
Good science and experiment design reduces error, but we can never get rid of it completely and some error always remains, so we have to accept and deal with it (hence replication and the use of inferential statistices etc.). We therefore adopt strategies that we know will reduce errors as much as possible.
Verification error is an important factor to consider here. This is also known as “confirmation bias” in the behavioral sciences ie. the process of trying to fit results to match preconceived ideas.
In psychology, social sciences, and human health sciences, results are naturally open to personal interpretation, especially for emotive issues, such as ethics, cultural perspectives or racism. A researcher must incorporate mechanisms to reduce the chance of confirmation bias, or risk losing validity and credibility.
You will most likely be aware of the concepts of validity and reliability:
Validity establishes whether the results obtained meet all of the requirements of the scientific research method.
Internal Validity is a measure of the accuracy of the scientific research in terms of the degree to which changes in the dependent variable can be attributed to manipulations of the independent variable. Here an experiment is said to possess internal validity if it properly demonstrates a causal relation between the variables. An experiment can demonstrate a causal relation by satisfying three criteria:
1) the “cause” precedes the “effect” in time (temporal precedence),
2) the “cause” and the “effect” are related (covariation), and
3) there are no alternative plausible explanations for the observed covariation (nonspuriousness)
A fun example is the Pirates and Global warming corrolation as depicted in this rather dubious graphical representation (from Venganza.org ) apart from the very dubious cause and effect link, what else is wrong with the graph?!:
External validity is the process of examining the results and questioning whether there are any other possible causal relationships. This is most difficult to achieve and asks the question of generalizability. I.e. To what populations, settings , treatment variables and measurement variables can an effect be generalized (Campbell & Stanley 1966)
Reliability is of course another aspect of minimizing errors. Here we are concerned that The results must be more than a one-off finding and repeatable. We must make sure the measurement tools we are using acurately measure what we are asking them to. Experiments are more difficult to repeat and are inherently less reliable.
Modern nursing research often focuses on qualitiative, humanistic, phenomenological approaches exploring subjective elements of phemonema, and the lived experience of individuals. This is certainly an important part of abductive and inductive process in scientific inquiry (Quiroz & Merrell, 2005) and produces outcomes that are not generalizable but that could be subject to further exploration and inform hypothesis development and experiment. However, many nursing researchers reject attempting to do this as positivisitic and reductionist in approach, arguing that we don’t need to generalize or reduce errors as the objective of this type of work is understanding the human experience which is not quantifiable. The classic argument being “you can’t measure love.” An example of this would be Doane & Varcoe (2007) who use this sort of approach, proposing “relational inquiry” as an alternative methodology in nursing science:
So this weeks question is: Why bother with quantification and error reduction at all in health research? As this approach is by its very nature subjective, and humanistic and surely a scientific quantification approach here would represent reductionism. Therefore error reduction has no part in modern humanistic research and any attempt at error reduction would seem a meaningless and fruitless exercise in this context. Thoughts?
Campbell, D.T., Stanley, J.C. (1966). Experimental and Quasi-Experimental Designs for Research. Skokie, Il: Rand McNally.
Doane G. H. Varcoe C.(2007) Relational Practice and Nursing Obligations. Advances in Nursing Science 30(3)
Quieroz J. & Merrell F. (2005) Abduction: Between Subjectivity and Objectivity, Semiotica 153 (1/4) 1–7.