Assignment: Two-way ANOVAs- Article Critique

The practice of quantitative research not only involves statistical calculations and formulas but also involves the understanding of statistical techniques related to real-world applications. You might not become a quantitative researcher nor use statistical methods in your profession but as a consumer, citizen, and scholar-practitioner, it will be important for you to become a critical consumer of research, which will empower you to read, interpret, and evaluate the strength of claims made in scholarly material and daily news.

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For this Assignment, you will critically evaluate a scholarly article related to factorial ANOVA.

To prepare

Review the Article Critique Assignment Guide in the Walden Library, listed in the Week 2 Learning Resources.
Search the Walden Library for a quantitative article that applies factorial analysis of variance. Note that sometimes these are referred to as “two-way ANOVAs.”

The Assignment

Write a 2- to 3-page critique of the research you found in the Walden Library that includes responses to the following prompts:

Why did the authors select factorial ANOVA in the research?
Do you think this test was the most appropriate choice? Why or why not?
Did the authors display the results in a figure or table?
Does the results table stand alone? In other words, are you able to interpret the study from it? Why or why not?

Note ALL AREAS MUST BE CITED AND REFERENCED IN APA

I am attaching an example please use an article of your choosing thanks

Assignment 1

Article Critiqued

Article: Li, S. D. (2011). Testing mediation using multiple regression and structural equation modeling analyses in secondary data. Evaluation review, 35(3), 240-268.

Why did the authors use mediation in their multiple regression model?

There are a couple of various alternatives one can browse to assess an intervention that demonstrate the use of Bootstrapping, which is turning into the most prominent technique for testing intercession since it doesn’t require the ordinary supposition to be met and because it can be viably be used with smaller specimen sizes (N < 25). Be that as it may, intercession keeps on being the most used when deciding to utilize the rationale of Baron and Kenny or the Sobel test (Li, 2011). Gunzler, Chen, Wu, and Zhang, (2013) explained that, “Baron and Kenny, in the first paper of addressing mediation analysis, tested the mediation process using a series of regression equations” (p. 391). Therefore, making it progressively harder to distribute trial of intercession construct which is absolutely on the Baron and Kenny strategy or criteria, which makes distributional presumptions; for example, the Sobel test. In this manner, it is essential to consider your choices when picking which test to lead.

Do you think mediation is the most appropriate choice? Why or why not?

Mediation is the best decision. Go-betweens efficiently handle many cases in which the gatherings either had no previous relationship (car collision), or don’t wish to save the relationship (separating either parent from their children). Still, different creators recognize those characteristics of a question or of the gatherings that will make intercession more efficient (Hayes, 2013). For example, they include a positive perspective, high confidence, satisfactory settlement expert, adaptability, persistence, reasonable desires, arrangement, an eagerness to tune in, a compelling transaction procedure, inventiveness, and trustworthiness.

As arbiters, legal advisors, and their customers acquire involvement with intervention, fewer parts of the debate will appear to be less manageable to the procedure (Hayes, 2013). Regardless of the possibility that intercession just prevails when looking at enhancing the gatherings’ correspondence, recognizing their primary advantages, narrowing the issues in conflict, or helping with the assessment for individuals to choose alternatives. Taking all this into consideration may assist the ensuing debates to progress at a faster pace, which is a financially sound determination.

The author provides an example of the circumstances that mediation is considered an essential factor:

When the gatherings have clashing perspectives of the actualities or law;
When a gathering need to express compelling feelings;
When a gathering pine for the chance to be heard correctly by the contradicting party;
When customers or their legal counselors can never again successfully speak with each other without the help of an apt go-between;
When the gatherings are not capable arbitrators and need the procedure structure and transaction ability given by ago between; or
When a contention exists between a group and his or her lawyer (Li, 2011).

Did the authors display the results in a figure or table?

The author displayed their results adequately in the form of a diagram (Li, 2011).

Does the results table stand alone? In other words, are you able to interpret the study from it? Why or why not?

When interpreting multiple regression to logistically, Garson (2014) explained that regression is used for “dichotomous and multinomial dependent variables, implemented with stand-alone logistic procedures or through generalized linear models” (p. 15). In this case, the resulting diagrams stands alone, which means that the interpretation part of it was easy to determine, and it clearly defines the relationship between the interacting variables to facilitate the mediation process.

References

Garson, G. D. (2014). MULTIPLE REGRESSION 2014 Edition – Statistical Associates. Retrieved June 16, 2017, from http://www.statisticalassociates.com/regression_p.pdf

Gunzler, D., Chen, T., Wu, P., & Zhang, H. (2013). Introduction to mediation analysis with structural equation modeling. Shanghai Archives of Psychiatry, 25(6), 390–394. http://doi.org/10.3969/j.issn.1002-0829.2013.06.009

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.

Li, S. D. (2011). Testing mediation using multiple regression and structural equation modeling analyses in secondary data. Evaluation review, 35(3), 240-268.