Comparing Three Preprocessing Strategies for Longitudinal Data

Longitudinal monitoring of individual patient data is becoming routine in physician office practice. This study compares three different methods for evaluating clinical outcomes for individual patients: raw change score analysis versus normative and ipsative statistical analyses. Two discrete samples of intermittent claudication patients making vascular surgery office visits—drawn from interventional management versus stable, routinely followed control groups—were tested four times using both generic and disease-specific functional status measures. Results indicated that the ipsative method was most consistent with several different types of a priori hypotheses that are often evaluated in analysis of repeated measures data.

[1]  P R Yarnold,et al.  Effects of actual waiting time, perceived waiting time, information delivery, and expressive quality on patient satisfaction in the emergency department. , 1996, Annals of emergency medicine.

[2]  A R Gilpin,et al.  Neural Network Simulation of Visual Inspection of Graphs of Single-Subject Interventions , 1996, Perceptual and motor skills.

[3]  W H Rogers,et al.  Differences in 4-year health outcomes for elderly and poor, chronically ill patients treated in HMO and fee-for-service systems. Results from the Medical Outcomes Study. , 1996, JAMA.

[4]  J. Feinglass,et al.  Effect of lower extremity blood pressure on physical functioning in patients who have intermittent claudication. The Chicago Claudication Outcomes Research Group. , 1996, Journal of vascular surgery.

[5]  Paul R. Yarnold,et al.  Discriminating Geriatric and Nongeriatric Patients Using Functional Status Information: An Example of Classification Tree Analysis Via UniODA , 1996 .

[6]  William R. Nugent,et al.  Integrating Single-Case and Group-Comparison Designs for Evaluation Research , 1996 .

[7]  P. Yarnold.  Characterizing and Circumventing Simpson's Paradox for Ordered Bivariate Data , 1996 .

[8]  P. Greenbaum,et al.  Five methods for computing significant individual client change and improvement rates: support for an individual growth curve approach. , 1995, Journal of consulting and clinical psychology.

[9]  P. Yarnold,et al.  Virus induced erythema multiforme and Stevens-Johnson syndrome. , 1995, Allergy proceedings : the official journal of regional and state allergy societies.

[10]  E. Foa,et al.  PTSD and major depression: Methodological and treatment considerations in a single case design* , 1995 .

[11]  Kevin P. Weinfurt.  Multivariate analysis of variance. , 1995 .

[12]  Paul R. Yarnold,et al.  Reading and Understanding Multivariate Statistics , 1995 .

[13]  J. Feinglass,et al.  Functional outcomes far patients with intermittent claudication: Bypass surgery versus angioplasty versus noninvasive management , 1994 .

[14]  Robert C. Soltysik,et al.  Univariable Optimal Discriminant Analysis:One-Tailed Hypotheses , 1994 .

[15]  S. Tanenbaum,et al.  Knowing and acting in medical practice: the epistemological politics of outcomes research. , 1994, Journal of health politics, policy and law.

[16]  John E. Ware,et al.  SF-36 physical and mental health summary scales : a user's manual , 1994 .

[17]  J. Feinglass,et al.  Prevalence of Walking Impairment in Young, Healthy Adults , 1993, Perceptual and motor skills.

[18]  Robert C. Soltysik,et al.  Theoretical Distributions of Optima for Univariate Discrimination of Random Data , 1991 .

[19]  P. Yarnold,et al.  Statistical Analysis for Single-Case Designs , 1991, Behavior modification.

[20]  P. Guttorp,et al.  The Taming of Chance. , 1992 .

[21]  D A Redelmeier,et al.  Discrepancy between medical decisions for individual patients and for groups. , 1990, The New England journal of medicine.

[22]  P. Yarnold.  Classical Test Theory Methods for Repeated-Measures N = 1 Research Designs , 1988 .

[23]  J. Zubin.  A technique for measuring like-mindedness. , 1938 .

[24]  L. Farrand.  THE AMERICAN PSYCHOLOGICAL ASSOCIATION. , 1897, Science.