Partial correlation is a form of analysis that works to find a correlation between two or more variables once the effects of other variables have been removed allowing for the researcher to either find relationships between the variables that would have been hidden as a result of the removed variables or allows the researcher to find the connections that would be explained by the effects of those other variables.

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An example of a quantitative nursing study that could be designed utilizing partial correlation could be the level of patient satisfaction with nursing staff care. Such a study would utilize the Likert Scale for initial data collection (Vanek, 2012), and it would be this collected data that would be analyzed. Though the data provided by the patients, their rating of the care, is an opinion, by utilizing a quantitative approach to this data and then a partial correlation analysis (Abeyasekera, n.d.), it will be possible to see the different characteristics embodied by the most preferred nurses in order to determine the true underlying reasons for patient preference in those nurses for care received. Partial correlation would be the most appropriate test to utilize in this study as it would allow the researchers to see the underlying relationships that may not otherwise be expressed.

The dependent variables would include the nurses who were working during the time that the patients were admitted and the fact that the patients were admitted. The independent variables are the practices of the nurses, and the quality of care offered. The confounding variables, those that are extraneous variables that may correlate with the results but are not the focus of the study (Price, n.d.), could include whether or not the nurse was having a good day, if the nurse was experiencing any personal issues that were affecting their care, if the nurse was new, or even whether or not the nurse or patient had enough sleep the night before.

  • Abeyasekera, S. (n.d.). 1 quantitative analysis approach es to qualitative data: why, when and how. [online] Retrieved from: [Accessed: 12 Feb 2014].
  • Price (n.d.). Confounding variables. [online] Retrieved from: [Accessed: 12 Feb 2014].
  • Vanek, C. (2012). Likert scale – what is it? when to use it? how to analyze it?. [online] Retrieved from: [Accessed: 12 Feb 2014].