Using HLM to Analyze Time Effects from Diverse Longitudinal Evaluation Studies: A New Method

2.50
Hdl Handle:
http://hdl.handle.net/10755/160911
Type:
Presentation
Title:
Using HLM to Analyze Time Effects from Diverse Longitudinal Evaluation Studies: A New Method
Abstract:
Using HLM to Analyze Time Effects from Diverse Longitudinal Evaluation Studies: A New Method
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2006
Author:Wooldridge, Powhatan, PhD, Study Contact and Co-Investigator
P.I. Institution Name:University at Buffalo/SUNY
Title:Associate Professor
Contact Address:School of Nursing, 1132 Kimball Tower, Buffalo, NY, 14215, USA
Contact Telephone:716 636-0456
Co-Authors:Yow Wu Bill Wu, PhD, Associate Professor and Co-Investigator; Bradley R. Fulton, PhD; and Susan L. Saltzman, ND, Visiting Lecturer
There are a growing number of client education interventions that health care professionals teach as standardized packages. Powerful Tools for Caregivers (PTC) is a psychoeducational intervention, disseminated by Mather LifeWays Institute for Aging (MLIA), that seeks to improve the lives of family caregivers by providing them with strategies to take care of their own needs. Standard protocols of questions ("surveys") are sometimes used to evaluate such interventions The potential exists for combining data from diverse sites into a single evaluation. One problem that arises in attempting such evaluations is that those who attend the classes may not conscientiously respond to posttest measures, especially if these are repeated at several time points. A further problem is that different agencies are likely to use somewhat different time points for posttest measurement. Important methods problems include: 1. How best to analyze time effects in such studies, in anticipation of diverse posttest measurement points and a great deal of missing data? 2. How to use the results from large data bases to assist in the evaluation of smaller studies? Hierarchical Linear Modeling is well suited for such analyses. We will propose best practice strategies , then illustrate them by showing how data from two smaller studies (N = 40; baseline, one month post; and N = 80; baseline, immediate post, three months post, six months post) can be usefully combined with data from MLIA's much larger data base (N = 586; baseline, immediate post, six months post, twelve months post) to focus on the evaluation and comparison of common time related issues. These issues are estimating the immediate post treatment difference, and estimating the post treatment trend over time. [Poster Presentation]
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleUsing HLM to Analyze Time Effects from Diverse Longitudinal Evaluation Studies: A New Methoden_GB
dc.identifier.urihttp://hdl.handle.net/10755/160911-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Using HLM to Analyze Time Effects from Diverse Longitudinal Evaluation Studies: A New Method</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</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">Wooldridge, Powhatan, PhD, Study Contact and Co-Investigator</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University at Buffalo/SUNY</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Associate Professor</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">School of Nursing, 1132 Kimball Tower, Buffalo, NY, 14215, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">716 636-0456</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">pjw@buffalo.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Yow Wu Bill Wu, PhD, Associate Professor and Co-Investigator; Bradley R. Fulton, PhD; and Susan L. Saltzman, ND, Visiting Lecturer</td></tr><tr><td colspan="2" class="item-abstract">There are a growing number of client education interventions that health care professionals teach as standardized packages. Powerful Tools for Caregivers (PTC) is a psychoeducational intervention, disseminated by Mather LifeWays Institute for Aging (MLIA), that seeks to improve the lives of family caregivers by providing them with strategies to take care of their own needs. Standard protocols of questions (&quot;surveys&quot;) are sometimes used to evaluate such interventions The potential exists for combining data from diverse sites into a single evaluation. One problem that arises in attempting such evaluations is that those who attend the classes may not conscientiously respond to posttest measures, especially if these are repeated at several time points. A further problem is that different agencies are likely to use somewhat different time points for posttest measurement. Important methods problems include: 1. How best to analyze time effects in such studies, in anticipation of diverse posttest measurement points and a great deal of missing data? 2. How to use the results from large data bases to assist in the evaluation of smaller studies? Hierarchical Linear Modeling is well suited for such analyses. We will propose best practice strategies , then illustrate them by showing how data from two smaller studies (N = 40; baseline, one month post; and N = 80; baseline, immediate post, three months post, six months post) can be usefully combined with data from MLIA's much larger data base (N = 586; baseline, immediate post, six months post, twelve months post) to focus on the evaluation and comparison of common time related issues. These issues are estimating the immediate post treatment difference, and estimating the post treatment trend over time. [Poster Presentation]</td></tr></table>en_GB
dc.date.available2011-10-26T23:12:45Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T23:12:45Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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