In regression analysis, it is relatively necessary to have a correlation between the response and explanatory variables, but having correlations amongst explanatory variables is something undesired. This paper focuses on five methodologies for handling critical multicollinearity, they include: Partial Least Square Regression (PLSR), Ridge Regression (RR), Ordinary Least Square Regression (OLS), Least Absolute Shrinkage and Selector Operator (LASSO) Regression, and the Principal Component Analysis (PCA). Monte Carlo Simulations comparing the methods was carried out with the sample size greater than or equal to the levels (n>p) considered in most cases, the Average Mean Square Error (AMSE) and Akaike Information Criterion (AIC) values were computed. The result shows that PCR is the most superior and more efficient in handling critical multicollinearity problems, having the lowest AMSE and AIC values for all the sample sizes and different levels considered.
Bioethics involves the objective assessment of how others, including animals and the environment, are affected by our values, desires, and actions. Bioethics covers global ethics, a field that focuses on the connection between biology, ecology, medicine, and human values. In this study, the understanding of research ethics information among students at the University of Benin was determined; we accessed the research ethics training knowledge base to understand constraints on the proper use of bioethics and research ethics. We also have access to the knowledge transfer rate of research ethics training conducted at the University of Benin; and the level of understanding of ethics compared between different fields of study. Findings from the study indicated that the respondents performed better ( ̅ = 16.77, SD = 3.36) after they were exposed to ethics training, Results showed that there is a statistically significant and positive relationship between students' academic qualification and ethics knowledge/practice (r = 0.26; p < 0.05), Similarly, there is a statistically significant and direct relationship between students' research experience and their ethics knowledge (r = 0.19; p < 0.05). However, the model does not reliably predict research ethics knowledge and practice [F (6, 103) = 1.919, p > 0.05].
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