Modeling Individual Patient Count/Rate Data over Time with Applications to Cancer Pain Flares and Cancer Pain Medication Usage

ISSN Print: 2161-718X
ISSN Online: 2161-7198
www.scirp.net/journal/ojs
E-mail: [email protected]

Citations

"Modeling Individual Patient Count/Rate Data over Time with Applications to Cancer Pain Flares and Cancer Pain Medication Usage"
written by George J. Knafl, Salimah H. Meghani,
published by Open Journal of Statistics, Vol.11 No.5, 2021

has been cited by the following article(s):

[1]	Trajectories and predictors of high-occurrence pain flares in ambulatory cancer patients on opioids
	JNCI Cancer …, 2024

[2]	Adaptive Random Effects/Coefficients Modeling
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[3]	An Adaptive Approach for Hazard Regression Modeling
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[4]	Adaptive Conditional Hazard Regression Modeling of Multiple Event Times
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[5]	An Analysis of Birth Defects and Developmental Disabilities for Children of Participants of the Air Force Health Study
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[6]	An analysis of reproductive outcomes for conceptions of participants of the Air Force Health Study
	Reproductive Toxicology, 2023

[7]	Regression Modeling of Individual-Patient Correlated Discrete Outcomes with Applications to Cancer Pain Ratings
	Open journal of statistics, 2022

[1]	Trajectories and predictors of high-occurrence pain flares in ambulatory cancer patients on opioids JNCI Cancer Spectrum, 2024 DOI:10.1093/jncics/pkae003

[2]	Adaptive Random Effects/Coefficients Modeling Open Journal of Statistics, 2024 DOI:10.4236/ojs.2024.142009

[3]	An Adaptive Approach for Hazard Regression Modeling Open Journal of Statistics, 2023 DOI:10.4236/ojs.2023.133016

[4]	Adaptive Conditional Hazard Regression Modeling of Multiple Event Times Open Journal of Statistics, 2023 DOI:10.4236/ojs.2023.134025

[5]	An analysis of birth defects and developmental disabilities for children of participants of the Air Force Health Study Reproductive Toxicology, 2023 DOI:10.1016/j.reprotox.2023.108355

[6]	An analysis of reproductive outcomes for conceptions of participants of the Air Force Health Study Reproductive Toxicology, 2023 DOI:10.1016/j.reprotox.2023.108413