Best (but of t-forgotten) practices: checking assumptions concerning regression residuals12

Barker, Lawrence E; Shaw, Kate M

doi:10.3945/ajcn.115.113498

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Best (but of t-forgotten) practices: checking assumptions concerning regression residuals12

Published Date:

Jul 22 2015

Publisher's site:

http://dx.doi.org/10.3945/ajcn.115.113498 New Site Icon

Source:

Am J Clin Nutr. 102(3):533-539.

[PDF - 258.79 KB]

Details:

Personal Authors:

Barker, Lawrence E ; Shaw, Kate M ;

Keywords:

[+]

Pubmed ID:

26201816

Pubmed Central ID:

PMC4558311

Description:

The residuals of a least squares regression model are defined as the observations minus the modeled values. For least squares regression to produce valid CIs and P values, the residuals must be independent, be normally distributed, and have a constant variance. If these assumptions are not satisfied, estimates can be biased and power can be reduced. However, there are ways to assess these assumptions and steps one can take if the assumptions are violated. Here, we discuss both assessment and appropriate responses to violation of assumptions.

Document Type:

Journal Article

Collection(s):

CDC Public Access

Funding:

CC999999/Intramural CDC HHS/United States

Supporting Files:

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