Week 7 Discussion
Regression analysis is one of the statistical models used in estimating the relationship between variables. The researcher has the ability to determine the effect that an independent variable has on the dependent variable (Willis & Riley, 2017). For example, an increase in one or more values on the independent variable would have an effect on the dependent variable. This paper examines regression analysis was used by an author including its weaknesses and strengths.
Article Summary
The article authored by Hatakeyama et al., (2019) aimed at finding the relationship between quality of clinical practice guideline (CPGs) and overall assessment scores. This study considered the previous studies that had been done and published between 2011 and 2015. These selected studies were subjected through an independent valuation using AGREE II. The author analyzed the results using a regression analysis. For instance, the analysis included the effect that the six domains and 23 items has on the overall assessment. The study collected a total of 206 CPGs and correlated all the domains to the items on the overall assessment to determine the strength of the relationship before taking the regression analysis on the proposed items.
Use of Regression on the Article
The author decided to subject domain 3, domain 4, domain 5, and domain 6 of the regression analysis. Domain three represented rigor of development, domain four was for clarity of presentation, domain five was for applicability and finally domain 6 was for editorial independence. The analysis was majoring on how these domains influence the overall assessment (Hatakeyama et al., 2019). The analysis showed that all the domains had a significant relationship with the overall assessment. The author also found that four different items on AGREE II, which were item 8, 15, 19 and 22 had an effect on overall assessment. The regression analysis showed that the change in one unit of the items above had a significant change on the overall assessment which in this case acted as the dependent variable (Hatakeyama et al., 2019). Therefore, the improvement of overall assessment dependent on the increase and decrease of the items that acted as independent variables in this case.
Other statistical analysis that could have been used in the study is ANOVA analysis because it shows the strength of the relationship between the items selected. Besides, it allows the researcher to determine the effect that each dependent variables have on each other and how the relationship between the dependent variables can influence the study (Fontaine et al., 2019). Use of ANOVA tests in this study could have strengthened and relayed more information on the collection of items that could have a great impact on the overall assessment.
The strength of the regression analysis is on the ability of the author to examine more than one dependent variable. According to the study the author was interested in 22 items and their effect on overall assessment. The study is able to report on the influence of 22 items more easily as compared to other methods that could have been complex (Hatakeyama et al., 2019). Despite the strength that regression analysis has on the study, the method also has its weakness it lacks the ability to examine the relationship between the independent variables considered in the study.
Conclusion
Regression analysis is a powerful tool in assessing the relationship between dependent and independent variables. The author in the selected the study has the ability to evaluate which of the 22 items have a high or low effect on the overall assessment.
References
Fontaine, G., Cossette, S., Maheu-Cadotte, M. A., Deschênes, M. F., Rouleau, G., Lavallée, A., … & Mailhot, T. (2019). Effect of implementation interventions on nurses’ behaviour in clinical practice: a systematic review, meta-analysis and meta-regression protocol. Systematic reviews, 8(1), 1-10. https://doi.org/10.1186/s13643-019-1227-x
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