Editing Selection bias (section)

===Sampling bias===

[[Sampling bias]] is systematic error due to a non-[[random sample]] of a population,<ref>[http://www.medilexicon.com/medicaldictionary.php?t=10087 Medical Dictionary - 'Sampling Bias'] Retrieved on September 23, 2009</ref> causing some members of the population to be less likely to be included than others, resulting in a [[biased sample]], defined as a [[statistical sample]] of a [[statistical population|population]] (or non-human factors) in which all participants are not equally balanced or objectively represented.<ref>[http://medical-dictionary.thefreedictionary.com/Sample+bias TheFreeDictionary → biased sample]. Retrieved on 2009-09-23. Site in turn cites: Mosby's Medical Dictionary, 8th edition.</ref> It is mostly classified as a subtype of selection bias,<ref>[http://medical.webends.com/kw/Selection%20Bias Dictionary of Cancer Terms → Selection Bias]. Retrieved on September 23, 2009.</ref> sometimes specifically termed ''sample selection bias'',<ref name="ArdsChung1998">{{cite journal|last1=Ards|first1=Sheila|last2=Chung|first2=Chanjin|last3=Myers|first3=Samuel L.|title=The effects of sample selection bias on racial differences in child abuse reporting|journal=Child Abuse & Neglect|volume=22|issue=2|year=1998|pages=103–115|pmid= 9504213|doi=10.1016/S0145-2134(97)00131-2|doi-access=free}}</ref><ref name="CortesMohri2008">{{cite book|last1=Cortes|first1=Corinna|last2=Mohri|first2=Mehryar|last3=Riley|first3=Michael|last4=Rostamizadeh|first4=Afshin|title=Algorithmic Learning Theory |chapter=Sample Selection Bias Correction Theory |volume=5254|year=2008|pages=38–53|url=http://www.cs.nyu.edu/~mohri/postscript/bias.pdf|doi=10.1007/978-3-540-87987-9_8|series=Lecture Notes in Computer Science|isbn=978-3-540-87986-2|arxiv=0805.2775|citeseerx=10.1.1.144.4478|s2cid=842488}}</ref><ref name="CortesMohri2014">{{cite journal|last1=Cortes|first1=Corinna|last2=Mohri|first2=Mehryar|title=Domain adaptation and sample bias correction theory and algorithm for regression|journal=Theoretical Computer Science|volume=519|year=2014|pages=103–126|url=http://www.cs.nyu.edu/~mohri/pub/nsmooth.pdf|doi=10.1016/j.tcs.2013.09.027|citeseerx=10.1.1.367.6899}}</ref> but some classify it as a separate type of bias.<ref name="Fadem2009">{{cite book|last=Fadem|first=Barbara|title=Behavioral Science|url=https://books.google.com/books?id=f0IDHvLiWqUC|year=2009|publisher=Lippincott Williams & Wilkins|isbn=978-0-7817-8257-9|page=262}}</ref>

A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the [[external validity]] of a test (the ability of its results to be generalized to the rest of the population), while selection bias mainly addresses [[internal validity]] for differences or similarities found in the sample at hand. In this sense, errors occurring in the process of gathering the sample or cohort cause sampling bias, while errors in any process thereafter cause selection bias.

Examples of sampling bias include [[self-selection]], pre-screening of trial participants, discounting trial subjects/tests that did not run to completion and migration bias by excluding subjects who have recently moved into or out of the study area, [[Length time bias|length-time bias]], where slowly developing disease with better prognosis is detected, and [[lead time bias]], where disease is diagnosed earlier for participants than in comparison populations, although the average course of disease is the same.