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Application of Robust Statistical Methods for Sensitivity Analysis of Health-Related Quality of Life Outcomes

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Abstract

Background: Researchers often use conventional parametric procedures to test hypotheses of health-related quality of life (HRQL) mean equality across patient groups. However, these techniques are sensitive to the presence of skewed distributions and unequal group variances, which may characterize many HRQL measures. Purpose: To conduct a sensitivity analysis of conventional and robust approaches to test hypotheses of mean equality on HRQL measures for hematopoietic stem cell transplantation survivors and a healthy comparison group. Methods: The methods applied were the conventional parametric procedure of least-squares analysis of variance applied to the raw scores, the conventional parametric procedure applied to transformed data, and a robust approximate degrees of freedom parametric procedure utilizing trimmed means and Winsorized variances. Results: The choice of analysis method affected the conclusions about the null hypothesis of mean equality. More commonly observed, however, was a substantial difference in the value of the F-statistic and standard errors which was particularly evident in the measures with greater degrees of skewness and heterogeneity of variances. Conclusions: Robust statistical tests should be incorporated into sensitivity analyses when analyzing HRQL data.

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Abbreviations

ANOVA:

analysis of variance

ADF:

approximate degrees of freedom

CES-D:

Center for Epidemiologic Studies Depression Scale

Duke-SS:

Duke-UNC Social Support

ES:

effect size

HC:

healthy comparison

FACIT-Fatigue:

Functional Assessment of Chronic Illness Therapy-Fatigue

FACIT-Sp:

Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being

FACT-PWB:

Functional Assessment of Cancer Therapy-Physical Well-Being

HRQL:

health-related quality of life

HSCT:

hematopoietic stem cell transplantation

LS:

least squares

MOS-Family:

Medical Outcomes Study-Family Functioning

MOS-Sleep:

Medical Outcomes Study-Sleep Problems

PHQ:

Perceived Health Questionnaire

PTGI:

Posttraumatic Growth Inventory

SD:

standard deviation

SE:

standard error

SF-36:

Medical Outcomes Study 36-item Short Form

SF-36-GH:

SF-36 General Health Perceptions

SF-36-MH:

SF-36 Mental Health Index

SF-36-PF:

SF-36 Physical Functioning

SF-36-SF:

SF-36 Social Functioning

SIP-AB:

Sickness Impact Profile-Alertness Behavior

STAI:

State-Trait Anxiety Inventory-Trait Anxiety

UCLA-L:

UCLA Loneliness

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Authors and Affiliations

  1. Center on Outcomes, Research and Education (CORE), Evanston Northwestern Healthcare, 1001 University Place, Evanston, IL, 60201, USA

    Jennifer L. Beaumont, Kathleen J. Yost & Elizabeth A. Hahn

  2. Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada

    Lisa M. Lix

  3. Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL

    Kathleen J. Yost & Elizabeth A. Hahn

Authors
  1. Jennifer L. Beaumont
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  2. Lisa M. Lix
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  3. Kathleen J. Yost
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  4. Elizabeth A. Hahn
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Correspondence to Jennifer L. Beaumont.

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Beaumont, J.L., Lix, L.M., Yost, K.J. et al. Application of Robust Statistical Methods for Sensitivity Analysis of Health-Related Quality of Life Outcomes. Qual Life Res 15, 349–356 (2006). https://doi.org/10.1007/s11136-005-2293-1

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  • DOI: https://doi.org/10.1007/s11136-005-2293-1

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