For health-related quality of life and other longitudinal data, analysis should distinguish between truncation by death and data missing because of nonresponse

Brenda F. Kurland; Brian L. Egleston

doi:10.1200/JCO.2016.69.1220

For health-related quality of life and other longitudinal data, analysis should distinguish between truncation by death and data missing because of nonresponse

Brenda F. Kurland, Brian L. Egleston

Cancer Signaling and Microenvironment (CSM)

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Original language	English
Pages (from-to)	4449
Number of pages	1
Journal	Journal of Clinical Oncology
Volume	34
Issue number	36
DOIs	https://doi.org/10.1200/JCO.2016.69.1220
State	Published - Dec 20 2016

Keywords

Bias
Death
Humans
Longitudinal Studies
Quality of Life

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10.1200/JCO.2016.69.1220

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T1 - For health-related quality of life and other longitudinal data, analysis should distinguish between truncation by death and data missing because of nonresponse

AU - Kurland, Brenda F.

AU - Egleston, Brian L.

PY - 2016/12/20

Y1 - 2016/12/20

KW - Bias

KW - Death

KW - Humans

KW - Longitudinal Studies

KW - Quality of Life

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DO - 10.1200/JCO.2016.69.1220

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SN - 0732-183X

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SP - 4449

JO - Journal of Clinical Oncology

JF - Journal of Clinical Oncology

IS - 36

ER -

For health-related quality of life and other longitudinal data, analysis should distinguish between truncation by death and data missing because of nonresponse

Keywords

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