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Research Area of Interest
The research area of interest is to find out the efficacy of antihyperglycemic drugs among patients with diabetes. Since the ability of the body to regulate blood glucose level is subject to the age of individuals, the study sought to find out if the efficacy of a novel antihyperglycemic drug varies across the ages of patients with diabetes. In this view, repeated measures ANOVA seeks to establish if pharmacokinetics and pharmacodynamics of the antihyperglycemic drug vary among the three groups of patients, namely, children between the ages of 6 and 17 years, young adults between the ages of 18 years and 30 years, and adults between the ages of 31 years and 42 years. The study assessed the efficacy of the antihyperglycemic drug using the level of blood glucose level (mg/dL). To obtain reliable findings, the study used 25 patients and measured their levels of blood glucose four times in six months. Before the intervention, two months after intervention, four months after intervention, and six months after the intervention are the four levels of measurements across the period.
Description of Variables
The two variables that are applicable in the analysis of repeated measures ANOVA are the level of glucose in blood across the intervention period of six months and the age of diabetic patients. The level of glucose in blood a dependent variable, which assesses the efficacy of the antihyperglycemic drug for six months. The scale of measurement of the blood glucose level is an interval scale. The blood glucose level is a repeating variable as patients. It measures diabetic patients four times: before the intervention, two months after intervention, four months after intervention, and six months after the intervention. Age of the patients is a categorical variable that gives three levels of measurement for the study, namely, children (between the ages of 6 and 17 years), young adults (between the ages of 18 and 30 years), and adults (between 31 and 42 years. The scale of measurement of the age of patients is nominal, and it is a fixed factor because it comprises the three levels of measurement.
The Assumption of Sphericity
|Mauchly’s Test of Sphericity|
|Within Subjects Effect||Mauchly’s W||Approx. Chi-Square||df||Sig.||Epsilon|
On the SPSS output, one can check if the data violates the assumption of sphericity by looking at the significance value at the table of Mauchly’s Test of Sphericity. The analysis of the hypothetical data gives the above table, which indicates that Mauchly’s value is significant (p = 0.000). When the significance value of Mauchly’s test statistic is less than 0.05, it implies that the data violated the assumption of sphericity. According to Field (2013), violation of the assumption of sphericity invalidates multivariate outcomes in terms of F-statistic and increases the likelihood of the occurrence of type I error. Moreover, since the hypothetical data, three groups, post hoc analysis is appropriate. However, owing to the violation of the assumption of sphericity, the violation complicates multiple comparisons of blood glucose levels among diabetic patients of different ages. Overall, violation of the assumption of sphericity gives erroneous outcomes in multivariate analysis and complicates the interpretation of post hoc analysis.
Field, A. (2013). Discovering statistics using IBM SPSS Statistics. London: SAGE Publications.
Myatt, G. (2007). Making sense of data: A practical guide to exploratory data analysis and data mining. London: John Wiley & Sons.