Part 21. Give a plausible example of a three-variable rese…

Part 2 1. Give a plausible example of a three-variable research problem in which partial correlation would be a useful analysis. 2. Define 1, 2, and . Make sure that you indicate which of your three variables is the “controlled for” variable ( 2). 3. What results might you expect to obtain for this partial correlation, and how would you interpret your results (e.g., spurious correlation, mediation, moderation, and so on)?

1. A plausible example of a three-variable research problem where partial correlation would be a useful analysis could be studying the relationship between income, education level, and job satisfaction. In this case, the researcher is interested in understanding the relationship between income and job satisfaction while controlling for education level.

2. In this example, let’s designate income as variable 1, education level as variable 2, and job satisfaction as variable 3. The controlled variable, in this case, would be education level (variable 2).

3. Partial correlation allows us to examine the relationship between two variables while controlling for the influence of a third variable. In this example, the researcher could compute the partial correlation coefficient between income (variable 1) and job satisfaction (variable 3), controlling for education level (variable 2).

The expected results of this partial correlation would depend on the nature of the relationship between income, education level, and job satisfaction. If there is a significant positive partial correlation between income and job satisfaction after controlling for education level, it suggests that income has a direct impact on job satisfaction, independent of education level. This means that even when education level is taken into account, higher income tends to associate with higher job satisfaction.

However, if the partial correlation between income and job satisfaction is not significant or close to zero, it could indicate that the relationship between income and job satisfaction is spurious. In this case, education level may be a third-variable driving the association between income and job satisfaction. This implies that education level is the underlying factor that influences both income and job satisfaction.

Additionally, partial correlation analysis can also help identify whether there is mediation or moderation present in the relationship between income, education level, and job satisfaction. Mediation occurs when the effect of one variable (income) on another (job satisfaction) is mediated by a third variable (education level). If education level acts as a mediator between income and job satisfaction, controlling for education level should weaken or eliminate the direct relationship between income and job satisfaction. On the other hand, moderation occurs when the relationship between two variables (income and job satisfaction) is influenced by a third variable (education level). If education level acts as a moderator, the strength or direction of the relationship between income and job satisfaction may vary depending on different levels of education.

In summary, partial correlation analysis is a valuable tool in examining relationships between variables while controlling for the influence of other variables. By isolating the effects of specific variables, researchers can better understand the direct, indirect, or moderated relationships between variables in a three-variable research problem.