3.3.4. Results
For the purpose of finding a suitable function for benefits transfer, different meta-regression models become specified: (i) different functional forms (e.g., a simple linear form versus semi-log form); (ii) a fully specified model including all independent variables and a restricted model on grounds of statistical significance or econometric problems (e.g., multicollinearity); (iii) robust consistent standard errors to correct for heteroskedasticity.
As shown by the test for heteroskedasticity (see Table 3.7), a simple linear form has heteroskedasticity. There are several ways to correct for heteroskedasticity (e.g., GLS, WLS, robust consistent errors, and data transformation). For this study, robust consistent standard errors and data transformation (e.g., the log transformation of the dependent variable) are utilized. All independent variables initially are considered, even if later dropped on grounds of statistical significance or econometric problems (e.g., multicollinearity). Some variables (e.g., MSW and ACTIV) are dropped because the variables have multicollinearity and/or are statistically insignificant at the 20% level for optimizing the meta-regression transfer model (suggested by Rosenberger and Loomis (2001, 2003).
A wide range of diagnostic tests has been conducted on each regression for benefits transfer (suggested by Walton et al. 2006). The R^2 for the overall fit of the regression, hypothesis tests (F tests and t tests), and diagnostic works (e.g., skewness-kurtosis normality test, Ramsey’s RESET test for the specification error bias, heteroskedasticity test, and multicollinearity assessment) are reported.
The F test assesses the null hypothesis that all or some coefficients ( ) on the model’s explanatory variables equal zero i.e., 〖H_0: β 〗_1= β_2=⋯= β_k=0 for all or some coefficients (Wooldridge 2003). A linear restriction test on some coefficients is useful before dropping the variables when some variables are unreliable due to multicollinearity (Hamilton 2004).
An important issue when handling small samples is the potential for multicollinearity which has a high degree of linear relationships between explanatory variables (Walton et al. 2006). The high correlation between estimated coefficients on explanatory variables in small samples can produce possible concerns: (i) substantially higher standard errors with lower t statistics (a greater chance of falsely accepting the null hypothesis in standard significance tests); (ii) unexpected changes in coefficient magnitudes or signs; and (iii) statistically insignificant coefficients despite the high R^2 (Hamilton 2004). A number of tests to indicate the presence and severity of multicollinearity exist (e.g., Durbin-Watson tests, VIF, Tolerance, and a correlation matrix between estimated coefficients). One test is the variance inflation factor (VIF) which measures the degree to which the variance and standard error of an estimated coefficient increase because of the inclusion of the explanatory variable (i.
Milkovich, G., Newman, J., & Gerhart, B. (2014). Compensation (11 International ed.). New York: McGraw-Hill.
In a simple regression model, we are trying to determine if a variable Y is linearly dependent on variable X. That is, whenever X changes, Y also changes linearly. A linear relationship is a straight line relationship. In the form of an equation, this relationship can be expressed as
Wang, X., Mears, D. P., Spohn, C., & Dario, L. (2013). Assessing the Differential Effects of
Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. However this can lead to illusions or false relationships, so caution is advisable;[2] for example, correlation does not imply
Collected data were subjected to analysis of variance using the SAS (9.1, SAS institute, 2004) statistical software package. Statistical assessments of differences between mean values were performed by the LSD test at P = 0.05.
...s and the GLM model, thus showing an adequate measure for the different variables. The study notes the small sample size. This brings up an issue of external validity, and being able to generalize the results to a wider population outside of their college students (Cozby, 2009).
Meta-analysis was performed, using odds ratios for dichotomous outcomes and weighted mean differences (WMD) for continuous outcomes, with 95% confidence intervals. Primary outcomes were a red...
Ul-Haq, Z., Mackay, D. F., Fenwick, E., Pell, J. P. (2013). Meta-analysis of the association
(2010)-(States, Congressional Washington DC): Congress of the United Budget Office, Scholarly article Social Security- United States- Finance: retirement income; online Access: http://purl.access.gpo.gov/GPO/LPS, http://www.cbo.gov/publication/21547
Many employees when looking for a job or deciding whether to stay with their current employment often considers the employee benefits the company offers.
Andrew A. Brennan Analysis , Vol. 47, No. 4 (Oct., 1987), pp. 225-230 published by: Oxford University Press on behalf of The Analysis CommitteeArticle Stable URL;http://www.jstor.org.ezproxy.taylors.edu.my/stable/3328797
Slack, B. & Rodrigue, J.P. (2011). Cost/Benefit Analysis. Retrieved on July 8, 2011 from http://people.hofstra.edu/geotrans/eng/ch9en/meth9en/ch9m1en.html.
The organization is able to manage a high coverage of risks at relative low costs owing to the availability of highly skilled personnel in the company’s team of employees. This benefit also brings about another advantage of easing the financial burden of the organization (Johnson, 2016). Besides, effective employee benefit system offered by the organization could improve the general productivity. This benefit is attributed to the fact that employees tent to be more effective when they are given assurance of job security. In addition, workers become more productive when they and their families are given the desired security by the employer. The other benefit to the organization if it employs an effective compensation and benefits system entail benefits from premiums (Wayne, Shore, M., Bommer, & Tetrick, 2002). These premiums are typically tax deductibles as corporate expense. As such, a company that has an effective compensation and benefits system is likely save extra money for other
Establishing the direction of the causality between health and income has become one of the main issues in the field of health economics. An informal explanation of this causality is: “a lot of people ...
Regression analysis is a technique used in statistics for investigating and modeling the relationship between variables (Douglas Montgomery, Peck, &