2.50
Hdl Handle:
http://hdl.handle.net/10755/159430
Type:
Presentation
Title:
How To Analyze Binary Repeated Measures Data in Nursing Research
Abstract:
How To Analyze Binary Repeated Measures Data in Nursing Research
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2003
Author:Wooldridge, Yow-Wu
P.I. Institution Name:University at Buffalo/SUNY
Contact Address:SON, 920 Kimball Tower, Buffalo, NY, 14214, USA
Studies using repeated measures are often found in nursing literature. Among those variables which nursing researchers typically measure at different time points are blood pressure, quality of life, weight loss and many other physiological and psychological characteristics. In most situations, these variables are analyzed as interval or ratio scale measures. The issue of how to analyze binary repeated measures data has been insufficiently addressed in nursing literature. The purpose of this presentation is to introduce and compare different approaches to the appropriate presentation and analysis of binary repeated measures for use in nursing research. The Longitudinal Study of Aging 1984-1990 will be used to demonstrate how to use three different approaches to the analysis of binary repeated measures. The outcome variable will be "Do you have any hospitalization during the past 12 months?" The answer to this question is either "yes", "no", or missing due to deceased, no response or not interviewed. This same question was asked of each subject in 1984, 1986, 1988 and 1990. Special issues which will be discussed in the presentation include how to take missing data (which varied from year to year) into account and how to analyze the pattern of changes in hospitalization from 1984 to 1990. The first approach is to conduct separate logistic regression analyses at four different times. The second approach is to use two-level repeated measures model, with time nested within subject, and to use individual subject characteristics to analyze the pattern of hospital admissions. The last approach is to use a multi-level multivariate logistic model with age, gender, major health condition and function of daily activities as independent variables which may influence the pattern of hospital admissions of a subject. AN: MN030190
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.titleHow To Analyze Binary Repeated Measures Data in Nursing Researchen_GB
dc.identifier.urihttp://hdl.handle.net/10755/159430-
dc.description.abstract<table><tr><td colspan="2" class="item-title">How To Analyze Binary Repeated Measures Data in Nursing Research </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">2003</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Wooldridge, Yow-Wu</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-address"><td class="label">Contact Address:</td><td class="value">SON, 920 Kimball Tower, Buffalo, NY, 14214, USA</td></tr><tr><td colspan="2" class="item-abstract">Studies using repeated measures are often found in nursing literature. Among those variables which nursing researchers typically measure at different time points are blood pressure, quality of life, weight loss and many other physiological and psychological characteristics. In most situations, these variables are analyzed as interval or ratio scale measures. The issue of how to analyze binary repeated measures data has been insufficiently addressed in nursing literature. The purpose of this presentation is to introduce and compare different approaches to the appropriate presentation and analysis of binary repeated measures for use in nursing research. The Longitudinal Study of Aging 1984-1990 will be used to demonstrate how to use three different approaches to the analysis of binary repeated measures. The outcome variable will be &quot;Do you have any hospitalization during the past 12 months?&quot; The answer to this question is either &quot;yes&quot;, &quot;no&quot;, or missing due to deceased, no response or not interviewed. This same question was asked of each subject in 1984, 1986, 1988 and 1990. Special issues which will be discussed in the presentation include how to take missing data (which varied from year to year) into account and how to analyze the pattern of changes in hospitalization from 1984 to 1990. The first approach is to conduct separate logistic regression analyses at four different times. The second approach is to use two-level repeated measures model, with time nested within subject, and to use individual subject characteristics to analyze the pattern of hospital admissions. The last approach is to use a multi-level multivariate logistic model with age, gender, major health condition and function of daily activities as independent variables which may influence the pattern of hospital admissions of a subject. AN: MN030190</td></tr></table>en_GB
dc.date.available2011-10-26T22:00:26Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T22:00:26Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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