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Calibration and seasonal adjustment for matched case–control studies of vitamin D and cancer

Overview of attention for article published in Statistics in Medicine, January 2016
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Title
Calibration and seasonal adjustment for matched case–control studies of vitamin D and cancer
Published in
Statistics in Medicine, January 2016
DOI 10.1002/sim.6856
Pubmed ID
Authors

Mitchell H Gail, Jincao Wu, Molin Wang, Shiaw-Shyuan Yaun, Nancy R Cook, A Heather Eliassen, Marjorie L McCullough, Kai Yu, Anne Zeleniuch-Jacquotte, Stephanie A Smith-Warner, Regina G Ziegler, Raymond J Carroll

Abstract

Vitamin D measurements are influenced by seasonal variation and specific assay used. Motivated by multicenter studies of associations of vitamin D with cancer, we formulated an analytic framework for matched case-control data that accounts for seasonal variation and calibrates to a reference assay. Calibration data were obtained from controls sampled within decile strata of the uncalibrated vitamin D values. Seasonal sine-cosine series were fit to control data. Practical findings included the following: (1) failure to adjust for season and calibrate increased variance, bias, and mean square error and (2) analysis of continuous vitamin D requires a variance adjustment for variation in the calibration estimate. An advantage of the continuous linear risk model is that results are independent of the reference date for seasonal adjustment. (3) For categorical risk models, procedures based on categorizing the seasonally adjusted and calibrated vitamin D have near nominal operating characteristics; estimates of log odds ratios are not robust to choice of seasonal reference date, however. Thus, public health recommendations based on categories of vitamin D should also define the time of year to which they refer. This work supports the use of simple methods for calibration and seasonal adjustment and is informing analytic approaches for the multicenter Vitamin D Pooling Project for Breast and Colorectal Cancer. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 14%
Researcher 3 14%
Student > Ph. D. Student 3 14%
Student > Bachelor 2 10%
Student > Doctoral Student 1 5%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 5 24%
Mathematics 2 10%
Nursing and Health Professions 2 10%
Social Sciences 2 10%
Agricultural and Biological Sciences 1 5%
Other 2 10%
Unknown 7 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 May 2016.
All research outputs
#22,024,252
of 24,571,708 outputs
Outputs from Statistics in Medicine
#3,597
of 4,026 outputs
Outputs of similar age
#343,841
of 403,666 outputs
Outputs of similar age from Statistics in Medicine
#82
of 84 outputs
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