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Category Archives: Data Analysis

Article by Bai, Haiyan and Pan, Wei (2008) in International Journal of Research & Method in Education, 31:1.

 

If you’re looking for a paper that describes all the resampling techniques in a non-mathematical way, this paper is the answer. It provides a brief description of each individual technique, plus the comparison on the strength, limitation and application aspects of all the techniques. It also provides examples of the application of each technique in the field of education research. All explained in a less-technical language for less-statistical-background readers.

 

Resampling is “a technique that creates multiple resamples from the original sample and derives statistics from these resamples”. [Note: For alternative definition, you may refer to wikipedia here]. It has two main purposes:

  1. To provide solutions for non-parametric and small-sample problems, where researchers will be able to: (a) quantify uncertainty by calculating standard errors and confidence intervals; and (b) perform significance tests with lessened assumptions;
  2. To gain more valid statistical results where sampling error can be reduced.

 

I prepare a table to illustrate the brief description of all the techniques below:

Resampling Techniques

Resampling Techniques

 

 

 

 

 

Article by Wood, Robert E.; Goodman, Jodi S.; Beckmann, Nadin; Cook, Alison (2008) in Organizational Research Methods, 11:2.

 

Do you know that there are 14 different ways to analyze for mediation, intervening variables and indirect effects? To be honest to myself, my answer is “I don’t”!! Before I read this paper, I knew only two ways to conduct such testing, one by using hierarchical regression and another one by using SEM (structural equation modeling). This paper outlines 14 different ways and divides them into three main frameworks, i.e. (i) the causal step approach; (ii) differences in coefficients, and; (iii) products of coefficients. The two methods that I previously knew, they are under the causal step framework. So what I knew was only two methods under one framework, and I didn’t know the other 12 methods. I didn’t even know the existence of the other two frameworks!!!

 

For me, it certainly shows how infinitely-massive is the planet named “knowledge” and how tiny I am in one of the planet’s island, named “research methodology”!!! How about you?

 

I summarize the three frameworks in a diagram at the end of this entry.

 

In this paper, the authors studied all articles that reported mediation testing in the 5 established journals over the past 25 years. Some of the findings (that for me are really interesting) are listed below:

  1. The trend indicated that the number of research with mediation analysis was increasing (within the 25 years study);
  2. Two approaches that mostly cited as the guidance for mediation analysis were Baron and Kenny’s approach (Baron and Kenny, 1986) and James and Brett’s approach (James and Brett, 1984);
  3. Two frameworks that mostly used to conduct the mediation analysis were Causal Steps approach and Product of Coefficients approach. For Product of Coefficients, the mostly cited approach was Sobel’s approach (Sobel, 1982);
  4. Regression has been the most common statistical test used for testing mediation, but the trend depicted the used of SEM (structural equation modeling) has grown significantly over time;
  5. Majority of the study demonstrated nonsignificant results for the inferences of mediation;
  6. Many of the studies were not adhere to the recommended testing procedure; therefore the findings are exposed to a certain degree of potential threats to the validity. They reported that they used certain framework, but failed to fully adhere to any of the recommended approach under the said framework. For instance, they claimed that they used Causal Step framework, but their works didn’t appear to adhere to any approach in the framework they used – either Baron & Kenny (1986) or Kenny, Kashy & Bolger (1998) or James & Brett (1984) or etc. etc.;
  7. Many studies put the basis of their claims of full or partial mediation on the change in the magnitude of coefficient without testing the significance of that change – this would definitely cause potential threats to validity;
  8. Another potential threat to validity was that, the researchers used the simple mediation model (one independent, one mediator and one dependent variables; X ® M ® Y) to test complex models (such as model with more than one mediator);
  9. Many studies made causal claims although conditions for causality were not met (researchers were supposed to use noncausal language and discuss effects in terms of covariation).
  10. The authors suggested a table format for reporting the Causal Steps mediation result which uses regression and the Sobel (1982) test. The table format is shown in a diagram below.

 

 

Mediation Analysis Frameworks

Mediation Analysis Frameworks

Reporting Mediation Result

Reporting Mediation Result

 

 

 

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