Repeated Measures in Healthcare Research Coursework

Exclusively available on Available only on IvyPanda®
This academic paper example has been carefully picked, checked and refined by our editorial team.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment

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
Measure: MEASURE_1
Within Subjects EffectMauchly’s WApprox. Chi-SquaredfSig.Epsilon
Greenhouse-GeisserHuynh-FeldtLower-bound
Months.17635.9975.000.496.572.333

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.

References

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.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2020, June 27). Repeated Measures in Healthcare Research. https://ivypanda.com/essays/repeated-measures-in-healthcare-research/

Work Cited

"Repeated Measures in Healthcare Research." IvyPanda, 27 June 2020, ivypanda.com/essays/repeated-measures-in-healthcare-research/.

References

IvyPanda. (2020) 'Repeated Measures in Healthcare Research'. 27 June.

References

IvyPanda. 2020. "Repeated Measures in Healthcare Research." June 27, 2020. https://ivypanda.com/essays/repeated-measures-in-healthcare-research/.

1. IvyPanda. "Repeated Measures in Healthcare Research." June 27, 2020. https://ivypanda.com/essays/repeated-measures-in-healthcare-research/.


Bibliography


IvyPanda. "Repeated Measures in Healthcare Research." June 27, 2020. https://ivypanda.com/essays/repeated-measures-in-healthcare-research/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
Privacy Settings

IvyPanda uses cookies and similar technologies to enhance your experience, enabling functionalities such as:

  • Basic site functions
  • Ensuring secure, safe transactions
  • Secure account login
  • Remembering account, browser, and regional preferences
  • Remembering privacy and security settings
  • Analyzing site traffic and usage
  • Personalized search, content, and recommendations
  • Displaying relevant, targeted ads on and off IvyPanda

Please refer to IvyPanda's Cookies Policy and Privacy Policy for detailed information.

Required Cookies & Technologies
Always active

Certain technologies we use are essential for critical functions such as security and site integrity, account authentication, security and privacy preferences, internal site usage and maintenance data, and ensuring the site operates correctly for browsing and transactions.

Site Customization

Cookies and similar technologies are used to enhance your experience by:

  • Remembering general and regional preferences
  • Personalizing content, search, recommendations, and offers

Some functions, such as personalized recommendations, account preferences, or localization, may not work correctly without these technologies. For more details, please refer to IvyPanda's Cookies Policy.

Personalized Advertising

To enable personalized advertising (such as interest-based ads), we may share your data with our marketing and advertising partners using cookies and other technologies. These partners may have their own information collected about you. Turning off the personalized advertising setting won't stop you from seeing IvyPanda ads, but it may make the ads you see less relevant or more repetitive.

Personalized advertising may be considered a "sale" or "sharing" of the information under California and other state privacy laws, and you may have the right to opt out. Turning off personalized advertising allows you to exercise your right to opt out. Learn more in IvyPanda's Cookies Policy and Privacy Policy.

1 / 1