Statistical Significance

Statistical Significance

Article Analysis

The article “The Relationship Between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals” written by Messina, D., Scotti, D., Ganey, R., Zipp, G., & Mathis, L. and was published in Journal of Healthcare Management in 2009. This research paper studies the relationship between patient satisfaction and inpatient admissions among teaching and nonteaching hospitals. It is based on two variables, which are satisfaction and admissions. The descriptive analysis of the data depicts that the small sample size, cannot be convincingly accurate, therefore, nonparametric statistical testing was done (Messina et al, 2009). The Spearman coefficient of rank-order correlation is used to analyze relationships between the independent variable, which is the patient satisfaction and the dependent variable which is the admissions.

Spearman's rank correlation coefficient is a non-parametric method, which is used to study the statistical relations between phenomena. In this case, determined by the actual degree of parallelism between the two rows of quantitative traits under study and assesses the closeness established connection with a quantitative expression ratio. Spearman's rank correlation coefficient is a measure of the linear relationship between random variables. To assess the strength of association between the magnitude of the numerical values ??are not used, and the corresponding grades. This ratio determines the degree of closeness and connection direction signs. The coefficient ranges from +1 to -1. Absolute value characterizes the closeness of relationship, and the sign - orientation relationship between the two characters (Spatz, 2008).

When using the correlation coefficient conditionally evaluate closeness of relationship between variables, assuming the coefficient of 0.3 or less, the performance of weak closeness of the connection and the values ??of more than 0.4 but less than 0.7 - moderate closeness of the connection parameters, and values ??of 0.7 and more - indicators of high closeness of the connection (Spatz, 2008). Spearman rank correlation coefficient is slightly inferior to the power of parametric correlation coefficient. The correlation coefficient is useful when there are few observations. This method can be used not only to quantify the data, but also in cases where the recorded values ??are determined by the descriptive attributes of varying intensity.

The advantage of spearman's rank coefficient correlation is that it can be ranked on the grounds that cannot be expressed numerically: value judgments, preferences, etc. When expert opinion can be ranked assessments of different experts and find their correlation with each other, only to be excluded from consideration to the experts, is weakly correlated ...