Size and Power Assessment of Tests of Hypotheses on Survival Parameters

Karl E. Peace; Roger E. Flora

doi:10.1080/01621459.1978.10480015

Size and Power Assessment of Tests of Hypotheses on Survival Parameters

Karl E. Peace, Roger E. Flora

Biostatistics, Epidemiology & Environmental Health Sciences

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

22 Scopus citations

Abstract

Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made. The test statistics arise from the likelihood ratio criterion and the asymptotic normality property of maximum likelihood estimators.

Original language	American English
Journal	Journal of the American Statistical Association
Volume	73
DOIs	https://doi.org/10.1080/01621459.1978.10480015
State	Published - 1978

Disciplines

Public Health
Biostatistics

Keywords

Concomitant information
Cox's form of the hazard
Failure and censored times
Failure density function
Hazard function
Maximum likelihood estimation
Size and power of tests of hypotheses on survival parameters
Survival function

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10.1080/01621459.1978.10480015License: Unspecified

Cite this

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title = "Size and Power Assessment of Tests of Hypotheses on Survival Parameters",

abstract = " Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made. The test statistics arise from the likelihood ratio criterion and the asymptotic normality property of maximum likelihood estimators.",

keywords = "Concomitant information, Cox's form of the hazard, Failure and censored times, Failure density function, Hazard function, Maximum likelihood estimation, Size and power of tests of hypotheses on survival parameters, Survival function",

author = "Peace, {Karl E.} and Flora, {Roger E.}",

note = "Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made.",

year = "1978",

doi = "10.1080/01621459.1978.10480015",

language = "American English",

volume = "73",

journal = "Journal of the American Statistical Association",

issn = "0162-1459",

publisher = "Taylor and Francis Ltd.",

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T1 - Size and Power Assessment of Tests of Hypotheses on Survival Parameters

AU - Peace, Karl E.

AU - Flora, Roger E.

N1 - Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made.

PY - 1978

Y1 - 1978

N2 - Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made. The test statistics arise from the likelihood ratio criterion and the asymptotic normality property of maximum likelihood estimators.

AB - Assuming the time-dependent component of Cox's form of the hazard function to be specified by the constant, Weibull, and Gompertz, produces three failure density models. Using simulation techniques, size and power comparisons between tests of hypotheses (concerning the regression parameters) arising from Cox's nonparametric method and tests arising from the three parametric models are made. The test statistics arise from the likelihood ratio criterion and the asymptotic normality property of maximum likelihood estimators.

KW - Concomitant information

KW - Cox's form of the hazard

KW - Failure and censored times

KW - Failure density function

KW - Hazard function

KW - Maximum likelihood estimation

KW - Size and power of tests of hypotheses on survival parameters

KW - Survival function

UR - https://doi.org/10.1080/01621459.1978.10480015

U2 - 10.1080/01621459.1978.10480015

DO - 10.1080/01621459.1978.10480015

M3 - Article

SN - 0162-1459

VL - 73

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

ER -

Size and Power Assessment of Tests of Hypotheses on Survival Parameters

Abstract

Disciplines

Keywords

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