Variance computations for functionals of absolute risk estimates

R. M. Pfeiffer; E. Petracci

doi:10.1016/j.spl.2011.02.002

Variance computations for functionals of absolute risk estimates

R. M. Pfeiffer, E. Petracci

Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori

Research output: Contribution to journal › Article

Abstract

We present a simple influence function based approach for computing the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Original language	English
Pages (from-to)	807-812
Number of pages	6
Journal	Statistics and Probability Letters
Volume	81
Issue number	7
DOIs	https://doi.org/10.1016/j.spl.2011.02.002
Publication status	Published - Jul 2011

Fingerprint

Keywords

Absolute risk
Bootstrap
Functional delta method

ASJC Scopus subject areas

Statistics, Probability and Uncertainty
Statistics and Probability

Cite this

Pfeiffer, R. M., & Petracci, E. (2011). Variance computations for functionals of absolute risk estimates. Statistics and Probability Letters, 81(7), 807-812. https://doi.org/10.1016/j.spl.2011.02.002

@article{4191195225fd4ad38f0b7177b0971105,

title = "Variance computations for functionals of absolute risk estimates",

abstract = "We present a simple influence function based approach for computing the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.",

keywords = "Absolute risk, Bootstrap, Functional delta method",

author = "Pfeiffer, {R. M.} and E. Petracci",

year = "2011",

month = jul

doi = "10.1016/j.spl.2011.02.002",

language = "English",

volume = "81",

pages = "807--812",

journal = "Statistics and Probability Letters",

issn = "0167-7152",

publisher = "Elsevier",

number = "7",

}

TY - JOUR

T1 - Variance computations for functionals of absolute risk estimates

AU - Pfeiffer, R. M.

AU - Petracci, E.

PY - 2011/7

Y1 - 2011/7

N2 - We present a simple influence function based approach for computing the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

AB - We present a simple influence function based approach for computing the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

KW - Absolute risk

KW - Bootstrap

KW - Functional delta method

UR - http://www.scopus.com/inward/record.url?scp=79955163222&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79955163222&partnerID=8YFLogxK

U2 - 10.1016/j.spl.2011.02.002

DO - 10.1016/j.spl.2011.02.002

M3 - Article

AN - SCOPUS:79955163222

VL - 81

SP - 807

EP - 812

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 7

ER -

Access to Document

10.1016/j.spl.2011.02.002