In addition to providing descriptive statistics on educational benefit programs and opinions about the programs, this study was designed to assess differences in educational benefits across employer characteristics. Further, small employers had fewer than 500 employees, medium employers had between 500 and 2,499 employees and large employers had 2,500 or more employees. Employer characteristics are often referred to as demographic or independent variables. Researchers can no more control which employers are from what industry or how many employees they employ, than they can control the gender or eye color of an employee. Because relational variables lack experimental manipulation, explaining differences in DVs by employer characteristics focuses on directional observations and associations of strengths or weaknesses, and not necessarily cause and effect relationships.
Logistic regression is a nonlinear form of regression.
Instead of using coefficients for model variables to predict outcomes based on different values with IVs, logistic regression uses logit estimates for variables to arrive at probability and odds-ratio estimates based on different values with IVs. While linear regression models also emphasize the amount of variability explained by each predictor variable and the model, logistic regression models generally do not provide this information. The omnibus or overall test examined the impact of industry, employer size and geographical region on the likelihood of having an educational benefit program. The resulting model with industry and employer size was significant. The logistic regression model was tested to ensure the variables were appropriate.