colinearity


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colinearity

[kō‚lin·ē′ar·əd·ē]
(cell and molecular biology)
The relationship between the linear sequence of codons in deoxyribonucleic acid and the order of amino acids in the polypeptide product that it specifies. Also spelled collinearity.
References in periodicals archive ?
If [r.sub.12] is high, then this colinearity can increase standard errors in real-world analyses and make the estimates unstable, although not biased in the statistical sense of expectation (Schisterman et al.
Thus, there is no colinearity among the selected descriptors, and the obtained model is stable.
Some facts can also show that more sample data can increase estimation accuracy relieve colinearity, minute estimation error can result in significant effect, and different patterns can emerge, which may prove the fact that the nonlinear system remarkably depends on the system parameters and initial state.
Given that this regression model showed problems of colinearity due to the relationship between the different addictions, a stratified analysis was performed to detect the presence or non-presence of addiction to alcohol and cocaine.
Regarding colinearity, we can observe that all the variables have a tolerance index above 0.4, and the VIF is in all variables clearly below 10 and following Belsley's criteria, condition index indicates no colinearity.
Due to its advantage of dimension reduction, synthesis, and solving colinearity problems among independent variables, partial least squares regression (PLSR) has been proved as a robust and reliable approach in spectral quantitative research [7, 33-35].
Colinearity is in most cases unavoidable in spectroscopy, as there are significantly more variables (waveshifts) than samples (observations).
Regarding this correlation and in order to prevent colinearity, potassium was not entered in the multiple logistic model while sodium was present.
Measurements of location of body fat: An assessment of colinearity with body mass, adiposity and stature in female adolescents.
Dysmorphic osseous characteristics include colinearity of the upper portion of the sacrum and the iliac crests, noncircular anterior sacral foramina, residual upper sacral discs, etc.
(2) One of the assumptions of the multiple regression model is the lack of colinearity. It means that no variable provides the model with the information which is contained in other variables (Stanisz, 2007).
However, in this model, VIF is greater than 5 for almost all the predictors (except diastolic blood pressure) showing that there is problem concerning the predictors' colinearity.