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1. Collinear.
2. Genetics
a. Characterized by correspondence between the linear sequence of nucleotides in a gene and the linear sequence of amino acids in the protein coded for by that gene.
b. Characterized by correspondence between the linear sequence of genes in a chromosome and another spatial or temporal sequence, such as the order of expression of the genes.

co·lin′e·ar′i·ty (-ăr′ĭ-tē) n.


the state of being arranged in the same linear sequence
References in periodicals archive ?
Mass and age category were investigated in separate models because of some colinearity.
The results we observed must interpreted with caution because of the small population studied and the possibility of colinearity, since many of the variables correspond to activities with a similar potential for rodent exposure.
pylori infection, and antacid use to resolve colinearity issues with race.
Those risk factors independently associated with the disease were evaluated in multivariate analyses by using log-binomial regression models after we ascertained the absence of a significant multiple colinearity among the variables.
Because of the need to reduce colinearity, we did not analyze environmental variables with similar geographic distributions together in the same model.
Colinearity and interaction among variables were calculated by using standard statistical techniques.
Colinearity was examined by replacing variables with each other and examining the effect on the model.
Colinearity issues and sample size limit interpretation of models containing all SES and home characteristics variables, although race/ethnicity appeared to have significant associations with dust mite and cockroach levels that were independent of the other SES and home characteristics variables considered.
This creates colinearity problems, which could be difficult to address.
We restricted all models to participants who gave usable responses to all variables (n = 7,430) and assessed models for potential 2-way interactions, goodness of fit, and potential colinearity.
This introduces greater colinearity between it and a general ideology variable such as the Nominate scores, which in turn can cause a counfounding effect upon the coefficient of the ideology variable.
4, which indicates colinearity between these variables, were not included in the logistic regression model.