where x is the explanatory variable, y the response variable, and n the sample size.
In the equation above, y it is the dependent variable; x it is the explanatory variable; Z it is a series of control variables; μ i is the province-level fixed effects; γ t is the fixed effect of time; and ε it is other factors that might be effective but are not identified by in mode, which is assumed to be random.
Here, x i t is the explanatory variable vector given by left y_{t-1},left y_{t-1}l_{iy}},ldots1}^{(1)},ldots, u_{t-l_{i1}}^{(1)},ldots,u_{t-1}^{(p)},ldots, u_{t-l_{in}}^{(p)}right)^{T} with l i y,l i1,…,l i p being the maximum time lags of each variable, where g i is a link function, and β i is a coefficient vector for i=1,2.
Then, we built up two regression models: i. the expression profile of the mRNA is the dependent variable X and the expression profile of the miRNA is the explanatory variable Z; ii. the expression profile of the lncRNA is the dependent variable Y and the expression profile of the miRNA is the explanatory variable Z.
In this glm, female genotype is the explanatory variable and the male offspring number the response variable with a quasi-poisson error structure to correct for over-dispersion [ 38].
This ratio can thus be calculated as the antilog of the regression coefficient of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p_{ F}$$\end{document p F which is the explanatory variable.
Hb was the explanatory variable with the highest independent contribution to the prediction (highest t ratio) (Table 1).
Where x urban and x rural are the explanatory variable at their means for the urban and rural.
The regression slope of the linear regressor line, when smoothed levator activity was the criterion variable and the number of productions was the explanatory variable, was calculated in each condition.
The X ij are the explanatory variables determining vulnerability level.
