Sentence examples for regression of job from inspiring English sources

Table  5 presents the results of linear regression of job satisfaction and intent to stay in Malawi.

Table  4 presents the results of linear regression of job satisfaction and intent to stay in Afghanistan.

A linear regression analysis of job-satisfaction versus salary shows that whereas scientists who earned $150,000 rated their job satisfaction as "very good," scientists earning barely one-fifth as much were only slightly less satisfied.

The dependent variables in the two regressions are the rate of job mobility in one digit industry classification to any employment state but unemployment and the average log wage of paid employees in one digit industry classification.

Table 2 Regressions for job polarisation.

We used logistic regression to measure the key predictors of job satisfaction because the dependent variable (job satisfaction) was a binary variable, which made linear regression unsuitable.

d: multiple regressions performed between each dimension of job search/turnover and facet of job satisfaction separately (P < 0.10); e: for both job search and turnover, all significant job facets from 1st analysis entered simultaneously in second multiple regression (P < 0.05).

Multiple linear regressions showed that 5 facets of job satisfaction were significantly (P ≤ 0.10) and negatively correlated to levels of EE: "remuneration", "workload", "tasks", "continuing education" and "management", but only "remuneration" and "tasks" remained significant at P ≤ 0.05 in the second combined regression.

We use a multilevel mixed-effects logistic regression model to estimate the effect of job accessibility on the likelihood of being informally employed, controlling for individual and other area characteristics.

Logistic regression analyses identified the best predictors of job satisfaction and these are presented for each of the six organizations and for all organizations combined.

Interprofessional teamwork is a significant predictor of job satisfaction (standardized regression weight: β = .80; p < .001), but organizational culture is not (β = −.033; p = .57).57