Time Parameterizations in Cluster Randomized Trial Planning

Kelsey L. Grantham; Andrew B. Forbes; Stephane Heritier; Jessica Kasza

doi:10.1080/00031305.2019.1623072

Time Parameterizations in Cluster Randomized Trial Planning

Kelsey L. Grantham, Andrew B. Forbes, Stephane Heritier, Jessica Kasza

Research output: Contribution to journal › Comment / Debate › Research › peer-review

14 Citations (Scopus)

Abstract

Models for cluster randomized trials conducted over multiple time periods should account for underlying temporal trends. However, in practice there is often limited knowledge or data available to inform the choice of time parameterization of these trends, or to anticipate the implications of this choice on trial planning. In this article, we establish a sufficient condition for when the choice of time parameterization does not affect the form of the variance of the treatment effect estimator, thereby simplifying the planning of these trials.

Original language	English
Pages (from-to)	184-189
Number of pages	6
Journal	The American Statistician
Volume	74
Issue number	2
DOIs	https://doi.org/10.1080/00031305.2019.1623072
Publication status	Published - 2 Apr 2020

Keywords

Column space
Design matrix
Invariance

Access to Document

10.1080/00031305.2019.1623072

Cite this

@article{f50de6ec113541f980d20b7084e2d146,

title = "Time Parameterizations in Cluster Randomized Trial Planning",

abstract = "Models for cluster randomized trials conducted over multiple time periods should account for underlying temporal trends. However, in practice there is often limited knowledge or data available to inform the choice of time parameterization of these trends, or to anticipate the implications of this choice on trial planning. In this article, we establish a sufficient condition for when the choice of time parameterization does not affect the form of the variance of the treatment effect estimator, thereby simplifying the planning of these trials.",

keywords = "Column space, Design matrix, Invariance",

author = "Grantham, {Kelsey L.} and Forbes, {Andrew B.} and Stephane Heritier and Jessica Kasza",

year = "2020",

month = apr,

day = "2",

doi = "10.1080/00031305.2019.1623072",

language = "English",

volume = "74",

pages = "184--189",

journal = "The American Statistician",

issn = "0003-1305",

publisher = "Taylor & Francis",

number = "2",

}

TY - JOUR

T1 - Time Parameterizations in Cluster Randomized Trial Planning

AU - Grantham, Kelsey L.

AU - Forbes, Andrew B.

AU - Heritier, Stephane

AU - Kasza, Jessica

PY - 2020/4/2

Y1 - 2020/4/2

N2 - Models for cluster randomized trials conducted over multiple time periods should account for underlying temporal trends. However, in practice there is often limited knowledge or data available to inform the choice of time parameterization of these trends, or to anticipate the implications of this choice on trial planning. In this article, we establish a sufficient condition for when the choice of time parameterization does not affect the form of the variance of the treatment effect estimator, thereby simplifying the planning of these trials.

AB - Models for cluster randomized trials conducted over multiple time periods should account for underlying temporal trends. However, in practice there is often limited knowledge or data available to inform the choice of time parameterization of these trends, or to anticipate the implications of this choice on trial planning. In this article, we establish a sufficient condition for when the choice of time parameterization does not affect the form of the variance of the treatment effect estimator, thereby simplifying the planning of these trials.

KW - Column space

KW - Design matrix

KW - Invariance

UR - http://www.scopus.com/inward/record.url?scp=85068060676&partnerID=8YFLogxK

U2 - 10.1080/00031305.2019.1623072

DO - 10.1080/00031305.2019.1623072

M3 - Comment / Debate

AN - SCOPUS:85068060676

SN - 0003-1305

VL - 74

SP - 184

EP - 189

JO - The American Statistician

JF - The American Statistician

IS - 2

ER -

Time Parameterizations in Cluster Randomized Trial Planning

Abstract

Keywords

Access to Document

Other files and links

New methods and guidelines for the design, analysis and reporting of cluster-crossover and stepped wedge randomised trials in clinical and public health research

Cite this

Time Parameterizations in Cluster Randomized Trial Planning

Abstract

Keywords

Access to Document

Other files and links

Projects

New methods and guidelines for the design, analysis and reporting of cluster-crossover and stepped wedge randomised trials in clinical and public health research

Cite this