Strategies for the Statistical Analysis of Pilot Data: An Example from the Translating Best Practice in Non-drug Pain Management Study

2.50
Hdl Handle:
http://hdl.handle.net/10755/154401
Type:
Presentation
Title:
Strategies for the Statistical Analysis of Pilot Data: An Example from the Translating Best Practice in Non-drug Pain Management Study
Abstract:
Strategies for the Statistical Analysis of Pilot Data: An Example from the Translating Best Practice in Non-drug Pain Management Study
Conference Sponsor:Sigma Theta Tau International
Conference Year:2006
Author:Willey-Temkin, Cynthia, PhD
P.I. Institution Name:College of Pharmacy, University of Rhode Island
Title:Professor
Co-Authors:Susan Rossi, PhD, RN; Stephen Kogut, MBA, PhD
Objective: The objective is to examine the use of traditional and non-traditional statistical techniques for the analysis of pilot data. Data from a study that tested the effects of translating scientific advances in non-pharmacological pain management on outcomes in older adults undergoing knee replacement is used for illustration. Design. The overall evaluation research design of the project had 2 components: (1) A primary efficacy study (n = 137 using a 2 group, quasi-experimental design to determine the impact on pain intensity, functional ability, and patient satisfaction; and (2) A sub-study, using a single group (n = 47) pretest-posttest exploratory descriptive design to evaluate the tailored teaching intervention and to describe the changes in the patients' knowledge, attitudes, ability to use, and actual use of the three non-drug "best practice" protocols. The groups were compared at each of three points along the trajectory of nursing care: (a) at baseline admission on the day of surgery, (b) on the evening of postoperative day 3 before discharge from the surgical unit; and (c) on the day of discharge from the rehabilitation unit. The following topics will be examined using these data: a) Graphical analysis of pilot studies, b) Non-parametric versus parametric techniques for pilot study data, c) Transforming data to increase the power of statistical tests, and d) Using change scores as an alternative method for controlling for baseline differences. Conclusions: The analysis of pilot study data should not be limited to traditional statistical approaches, or simple counts of outcomes. Novel techniques such as change score transformations can increase power and allow detailed analyses of pilot data and other small sample studies.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleStrategies for the Statistical Analysis of Pilot Data: An Example from the Translating Best Practice in Non-drug Pain Management Studyen_GB
dc.identifier.urihttp://hdl.handle.net/10755/154401-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Strategies for the Statistical Analysis of Pilot Data: An Example from the Translating Best Practice in Non-drug Pain Management Study</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2006</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Willey-Temkin, Cynthia, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">College of Pharmacy, University of Rhode Island</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">cwilley@uri.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Susan Rossi, PhD, RN; Stephen Kogut, MBA, PhD</td></tr><tr><td colspan="2" class="item-abstract">Objective: The objective is to examine the use of traditional and non-traditional statistical techniques for the analysis of pilot data. Data from a study that tested the effects of translating scientific advances in non-pharmacological pain management on outcomes in older adults undergoing knee replacement is used for illustration. Design. The overall evaluation research design of the project had 2 components: (1) A primary efficacy study (n = 137 using a 2 group, quasi-experimental design to determine the impact on pain intensity, functional ability, and patient satisfaction; and (2) A sub-study, using a single group (n = 47) pretest-posttest exploratory descriptive design to evaluate the tailored teaching intervention and to describe the changes in the patients' knowledge, attitudes, ability to use, and actual use of the three non-drug &quot;best practice&quot; protocols. The groups were compared at each of three points along the trajectory of nursing care: (a) at baseline admission on the day of surgery, (b) on the evening of postoperative day 3 before discharge from the surgical unit; and (c) on the day of discharge from the rehabilitation unit. The following topics will be examined using these data: a) Graphical analysis of pilot studies, b) Non-parametric versus parametric techniques for pilot study data, c) Transforming data to increase the power of statistical tests, and d) Using change scores as an alternative method for controlling for baseline differences. Conclusions: The analysis of pilot study data should not be limited to traditional statistical approaches, or simple counts of outcomes. Novel techniques such as change score transformations can increase power and allow detailed analyses of pilot data and other small sample studies.</td></tr></table>en_GB
dc.date.available2011-10-26T12:58:12Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T12:58:12Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
All Items in this repository are protected by copyright, with all rights reserved, unless otherwise indicated.