# covariate

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## covariate

(ˈkəʊˌvɛərɪɪt)
n
(Statistics) a statistical variable that changes in a predictable way and can be used to predict the outcome of a study
Collins English Dictionary – Complete and Unabridged, 12th Edition 2014 © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003, 2006, 2007, 2009, 2011, 2014
References in periodicals archive ?
Together, these studies provide strong evidence for the causality of the association because they were conducted by multiple investigators in multiple countries, with a wide range of covariate control strategies.
An analysis of covariance with covariate adjustment revealed that undecided career planning students had lower adjusted mean scores on a measure of negative career thinking than the decided STEM majors after the first semester of college.
Table 1: Parameter estimates of the CD4 response model, based on the NLME and ELM covariate models respectively.
Spatial analysis with terrain attributes represented by numerical surface models as covariate to predict soil units were exemplified for McBratney et al.
Given the relatively weak AICc weight of our top detection model (AICc weight = 0.12), we conducted a post-hoc analysis to evaluate how selection of this model for use in modeling occupancy may influence the effect sizes of our occupancy covariates, specifically the covariate Rock (see Appendix I).
The final compartmental model included a categorical covariate to account for this lag in absorption as well as body weight as a covariate of total body clearance (relative to unknown bioavailability).
where t is the Time between Failures (a random variable) of NC machine tools; X = ([X.sub.1],[X.sub.2], ..., [X.sub.i], ..., [X.sub.n]), X is the vector of working condition covariates, which affects the failure rate of NC machine tools, and [X.sub.i] is the ith covariate, such as cutting force, environment temperature, and number of tool changes or vibration; m is the shape parameter under [X.sub.1], and m > 0; q is the scale parameter under [X.sub.1], [eta] > 0; [beta] = ([[beta].sub.1], [[beta].sub.2], ..., [[beta].sub.i], ..., [[beta].sub.n]) is the vector of X's coefficients, which reflect the covariates' influences on the failure rate function, and [[beta].sub.i] is the coefficient of [X.sub.i].
In order to solve this problem, we propose a joint covariate detection strategy for selection of variable pairs instead of a combination of variables individually correlated with survival time from expression profiles.
Adjustment for a covariate is explained in an article accompanying the spreadsheets that first included one covariate.
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