Panel data regression is applied in this study to identify the impact of dependent variables (Total Leverage and corporate ownership) and independent variables
(firm size, firm age, tax shield, growth opportunity, firm profitability, asset tangibility, assets maturity, earning volatility, corruption perceived index, dividend payout firm level investment and long term leverage).
Simulation with Three Independent Variables Independent variables
were derived from normal distributions as being [X.sub.1]~N(200,45), [X.sub.2]~N(130,30), [X.sub.3]~N(60,14) and correlated to one another ([r.sub.12]=0.704, [r.sub.13] =0.553, [r.sub.23]=0.372).
The multiple regression results indicate different values for each of the three independent variables
, which help in accepting and rejecting the hypotheses.
The correlation coefficient between the independent variables
shows that there is a multicollinearity problem if its absolute value is close to 1 (Albayrak, 2005).
In the future we shall further discuss the dynamic response to various perturbations (initial states, initial time, independent variables
, and dependent variables) and the second order sensitivity (showing the parameter sloppiness) at any time instant or around the steady state.
In this study all independent variables
are independent from each other.
A simple regression has one independent variable
paired with a dependent variable, while multiple regression can have two or more independent variables
with a dependent variable.
The performance of a PPV, aphakia after the initial trauma, the loss of iris tissue, a penetrating injury, and the cutting of any prolapsed vitreous in the primary surgery are the independent variables
with significant effects on the final visual outcome.
To acquire a well-trained machine learning model, in addition to the regular training and testing processes as shown in Sections 2.2 and 2.3, another key step is to define the independent variables
A cycle average map in terms of dependent variables, which could be BSFC or fuel mass as function of two independent variables
for each certification cycle, will be generated.
In case of direct causal effect of leadership styles on the dependent variable, job satisfaction, the significant path coefficients for H12, H13, H14, and H15 affirmed that all four independent variables
have direct effect on the level of job satisfaction.
Practically when we deal regression analysis and our dependent variable is categorical then we are not able to use simple linear or multiple linear regression, especially when dependent variable is binary (dichotomous) then we can use Logistic Regression and the independent variables
are of any type like categorical or continuous.