Chapter 8: Examining Relationships among Your Variables

Journal Article 1: Conn, V. S. (2017). Don’t rock the analytical boat: Correlation is not causation. Western Journal of Nursing Research, 39, 731–732. doi:10.1177/0193945917701090

Learning Objective: 8-1: The advantages and limits of correlational designs.

Summary: This is an editorial about mistaking correlation and causation.

Questions to Consider:

  1. According to the author, what are some of the reasons that researchers might misinterpret correlational results as causal results?
  2. What are some of the benefits of correlational research that the author identifies?
  3. What are some solutions to address the problem of mistaking correlation and causation in published research and reviews?

 

Journal Article 2: Eakman, A. M., Schmid, A. A., Henry, K. L., Rolle, N. R., Schelly, C., Pott, C. E., & Burns, J. E. (2017). Restoring effective sleep tranquility (REST): A feasibility and pilot study. British Journal of Occupational Therapy, 80, 350–360. doi:10.1177/0308022617691538

Learning Objectives: 8-1: The advantages and limits of correlational designs. | 8-2: How to distinguish between correlational design and correlation as a statistic.

Summary: This is a pilot correlational study on a sleep intervention.

Questions to Consider:

  1. Why did the authors conduct this pilot correlational study?
  2. Did the authors use any correlational statistics (Pearson’s r or point biserial r) identified in chapter 8 of the text? Why might this be?
  3. What are the results and implications of this study?

 

Journal Article 3: Johnson, R. R. (2012). Police officer job satisfaction: A multidimensional analysis. Police Quarterly, 15, 157–176. doi:10.1177/1098611112442809

Learning Objectives: 8-1: The advantages and limits of correlational designs. | 8-3: How to compute and interpret the statistics assessing correlations between variables of different measurement scales. | 8-4: How to predict scores of one variable based on another.

Summary: This is a study examining predictors of police officer job satisfaction.

Questions to Consider:

  1. Why is a correlational design the right design choice for this study?
  2. In Table 2, the authors report Pearson’s r correlation coefficients. In which cases is this the correct analysis, and in which cases should they have referred to the analysis as a point-biserial correlation?
  3. What was the purpose of conducting the regression analyses?