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Guidance for use of weights: an analysis of different types of weights and their implications when using SAS PROCs
  1. Sabrina Richardson1,2,
  2. Tuo Lin3,
  3. Yangyi Li4,
  4. Xiaohui Niu5,
  5. Manfei Xu6,
  6. Valerie Stander2 and
  7. Xin M Tu2,3
  1. 1 The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, Maryland, United States
  2. 2 Military Population Health, Naval Health Research Center, San Diego, Ca, United States
  3. 3 Clinical and Translational Research Institute, University of California San Diego, San Diego, California, USA
  4. 4 School of Mathematical and Statistical Sciences, Clemson University, Clemson, South Carolina, USA
  5. 5 College of Informatics, Huazhong Agriculture University, Wuhan, China
  6. 6 Shanghai Mental Health Center, Medical College, Shanghai Jiao Tong University, Shanghai, China
  1. Correspondence to Dr Xin M Tu; x2tu{at}ucsd.edu

Abstract

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures.

  • homoscedasticity
  • linear regression
  • statistical method
  • weights

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0

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Footnotes

  • Contributors SR, XN, VS, MX and XMT had extensive discussions of the statistical issues with different types of weights and their implementations in some popular statistical packages and worked together to structure this report. TL, YL and XN worked together to find the formulas for the estimate and SEs of the estimate of the population mean as implemented in SAS and developed the computer codes to perform data simulations and inference for the examples.

  • Funding The project described was partially supported by the National Institutes of Health, Grant UL1TR001442 of CTSA funding beginning 13 August 2015 and beyond and by the Navy Bureau of Medicine and Surgery under work unit no. N1240. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

  • Disclaimer I am an employee of the US Government. This work was prepared as part of my official duties. Title 17, U.S.C. §105 provides that copyright protection under this title is not available for any work of the US Government. Title 17, U.S.C. §101 defines a US Government work as work prepared by a military service member or employee of the US Government as part of that person’s official duties. This work was supported by the Navy Bureau of Medicine and Surgery under work unit no. N1240. The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense, nor the US Government.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Commissioned; internally peer reviewed.

  • Data sharing statement No additional data are available.

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