Literature DB >> 8745130

Study design for epidemiologic studies with measurement error.

T R Holford1, C Stack.   

Abstract

Exposure measurement error in epidemiological studies is recognized as a feature that must be considered because of the potential bias that can result in estimates of the exposure-disease association. Most of the work to date has focused on methods of analysis that adjust for the resultant bias, but the implications of this work to the design of epidemiologic studies is not as well understood. An overview of the issues involved in the use of methods for dealing with errors in exposure information is discussed along with some design options that have been proposed for providing information necessary for their use. Validation studies compare somewhat crude and inexpensive measures of exposure to a gold standard, and study designs that incorporate these into the overall plan can realize some advantages in terms of cost. In addition, repeated assessments of exposure can realize efficiency for measures of exposure that are unbiased. However, much work remains to be done in the development of efficient designs for studying disease aetiology and prevention.

Mesh:

Year:  1995        PMID: 8745130     DOI: 10.1177/096228029500400405

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  9 in total

Review 1.  Impact of measurement error in the study of sexually transmitted infections.

Authors:  L Myer; C Morroni; B G Link
Journal:  Sex Transm Infect       Date:  2004-08       Impact factor: 3.519

2.  Adjusting effect estimates for unmeasured confounding with validation data using propensity score calibration.

Authors:  Til Stürmer; Sebastian Schneeweiss; Jerry Avorn; Robert J Glynn
Journal:  Am J Epidemiol       Date:  2005-06-29       Impact factor: 4.897

3.  Two-Phase Sampling Designs for Data Validation in Settings with Covariate Measurement Error and Continuous Outcome.

Authors:  Gustavo Amorim; Ran Tao; Sarah Lotspeich; Pamela A Shaw; Thomas Lumley; Bryan E Shepherd
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2021-04-15       Impact factor: 2.175

Review 4.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Authors:  Ruth H Keogh; Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Helmut Küchenhoff; Janet A Tooze; Michael P Wallace; Victor Kipnis; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

5.  The Queensland Study of Melanoma: environmental and genetic associations (Q-MEGA); study design, baseline characteristics, and repeatability of phenotype and sun exposure measures.

Authors:  Amanda J Baxter; Maria Celia Hughes; Marina Kvaskoff; Victor Siskind; Sri Shekar; Joanne F Aitken; Adele C Green; David L Duffy; Nicholas K Hayward; Nicholas G Martin; David C Whiteman
Journal:  Twin Res Hum Genet       Date:  2008-04       Impact factor: 1.587

6.  Concordance between the TIRADS ultrasound criteria and the BETHESDA cytology criteria on the nontoxic thyroid nodule.

Authors:  Hernando Vargas-Uricoechea; Ivonne Meza-Cabrera; Jorge Herrera-Chaparro
Journal:  Thyroid Res       Date:  2017-02-02

Review 7.  Systematic review of statistical approaches to quantify, or correct for, measurement error in a continuous exposure in nutritional epidemiology.

Authors:  Derrick A Bennett; Denise Landry; Julian Little; Cosetta Minelli
Journal:  BMC Med Res Methodol       Date:  2017-09-19       Impact factor: 4.615

8.  Application of the Adaptive Validation Substudy Design to Colorectal Cancer Recurrence.

Authors:  Lindsay J Collin; Anders H Riis; Richard F MacLehose; Thomas P Ahern; Rune Erichsen; Ole Thorlacius-Ussing; Timothy L Lash
Journal:  Clin Epidemiol       Date:  2020-02-03       Impact factor: 4.790

9.  Adaptive Validation Design: A Bayesian Approach to Validation Substudy Design With Prospective Data Collection.

Authors:  Lindsay J Collin; Richard F MacLehose; Thomas P Ahern; Rebecca Nash; Darios Getahun; Douglas Roblin; Michael J Silverberg; Michael Goodman; Timothy L Lash
Journal:  Epidemiology       Date:  2020-07       Impact factor: 4.860

  9 in total

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