By : Praveen Kumar NeelappaThis article suggests that there is the gap between theory and practice in the use of analysis of competing hypotheses (ACH). It identifies several intellectual and practical barriers that discourage the use of multiple hypotheses in the field of ecology and evolution. This article points out that scientist have a bias or a motivation to consider one hypothesis over other (Intellectual barriers) and there are practical limitations inherent to factorial design, the standard experimental design that allows researchers to evaluate several explanatory variables and their interactions in the same study, one variable at a time (Practical barrier).
Cognitive bias makes us think that we are making a logical, rational and effective decision while considering the alternative hypothesis, but our unconscious bias influences the experiment and its outcome. There is a tendency of scientist to put more weight on evidence that supports favored ideas more than other evidence that is available (Confirmation bias), seek for the pattern in their experiment (Pattern seeking bias) and be judged only by their internal consistency (Belief bias). There are several ways one might minimize the effect of cognitive bias in science so that one does not rely exclusively on one’s perceptions. It can be achieved by masking (kept) information about the experiment from the participant, to reduce or eliminate bias, until after a trial outcome is known (Blind bias), working with other scientists with different perspectives (Work with the enemy) and a null model which generates a pattern in the absence of any biological process, forcing the researcher to think about many different hypotheses, which could potentially minimize the negative impacts of cognitive biases in science.
Any study that has a simple, easy to understand explanation will be preferred over a study that employs complex and perhaps less-elegant ideas (Simplicity bias) to avoid practical barrier. Editors and reviewers tend to rely on prior knowledge when evaluating a manuscript, creating additional difficulties for researchers when publishing studies that confront well-established ideas. This tension between new and old ideas could reflect a conflict between new and old generations (Publication bias).
The article concludes by suggesting that ecological and evolutionary research is aimed at understanding patterns arising from nonlinear and stochastic interactions among a multitude of processes and agents at multiple spatial and temporal scales. If we wish to truly advance scientific progress despite this complexity, we must better commit to strong inference in our scientific inquiries by simultaneously evaluating multiple competing hypotheses.
The use of ACH is widely promoted to enhance the effectiveness of the scientific investigation. This article points out some valid draw backs of using ACH in the different field of studies and discusses these drawbacks and solutions to them in detail. The article clearly illustrates various types of biases and the various stages where they can be encountered while carrying out experiments. It is imperative that the individual carrying out the experiment is objective in data collection and maintains an objective view at every stage of the experiment which will be the best way to counter any possibility of the final results being biased. Additionally, measures need to be put in place to reassess for bias along the way to ensure the results are void of any form of bias.
Betini GS, Avgar T, Fryxell JM. 2017 Why are we not evaluating multiple competing hypotheses in ecology and evolution?.R. Soc. open sci. 4: 160756. http://dx.doi.org/10.1098/rsos.160756