Phenomena of Inertia Bias in Research, Practicalities of Possible Adjustment

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In academic research, bias refers to a type of systematic error that can distort measurements and/or affect investigations and their results. Biases can be present in both quantitative and qualitative research. The common effect of biases is undermining the power of statistical tests, therefore findings induced to support H0 hypothesis. Corrections depend on nature of bias and aimed to recover magnitude of association. Corrections use analytical constructs therefore applied in data analysis stage. Considered in the paper is of novel type and tentatively named inertia bias. This bias is of directed uncertainty about true value of index. One can find it in the range of designs and measures. The essence is the exposure takes time to shift index to new equilibrium. The problem is that researcher usually unaware of time required for index to settle down at new equilibrium. Therefore one inevitably measures the transition states instead of equilibrium yielding different magnitudes of attenuated association. How to obtain measure equilibrium value is the focus of the paper. Given the dynamical setup I referred to first order nonlinear differential equations, in particular logistic differential equation that meats necessary prerequisites: it should be separable equation, it has to have stable state, solutions have to descend or ascend toward equilibrium with the tangency in time. This paper describes range of circumstances where researcher faces the problem along with suggested solution, calculus, and tested software.