更改

在'''<font color="#ff8000"> 临床试验 Clinical trials </font>'''中，根据患者的社会和个人背景或与研究相关的任何因素对患者进行分层，以匹配整个患者群体中的每个组。 这样做的目的是建立临床/预后因素（prognostic factor）的平衡，因为如果研究设计不平衡，试验将不会产生有效的结果。<ref>{{Cite book|last1=Polit|first1=DF|title=Nursing Research: Generating and Assessing Evidence for Nursing Practice, 9th ed.|last2=Beck|first2=CT|publisher=Lippincott Williams & Wilkins.|year=2012|location=Philadelphia, USA: Wolters Klower Health}}</ref>  分层随机化的步骤非常重要，因为它试图确保没有偏见、有意或无意地影响所研究患者样本的代表性。 <ref>{{Cite web|url=https://www.omixon.com/patient-stratification-in-clinical-trials/|title=Patient Stratification in Clinical Trials|date=2014-12-01|website=Omixon {{!}} NGS for HLA|language=en-US|access-date=2020-04-26}}</ref>  它增加了研究能力，尤其是在小型临床试验中（n<400），因为这些已知的临床特征分层被认为会影响干预的结果。<ref>{{Cite web|url=https://www.statisticshowto.com/stratified-randomization/|title=Stratified Randomization in Clinical Trials|last=Stephanie|date=2016-05-20|website=Statistics How To|language=en-US|access-date=2020-04-26}}</ref>它有助于防止在临床研究中受到高度重视的 '''<font color="#ff8000"> I 型错误 Type I error </font>'''的发生。 <ref name=":6">{{Cite journal|last=Kernan|first=W|date=Jan 1999|title=Stratified Randomization for Clinical Trials|journal=Journal of Clinical Epidemiology|volume=52|issue=1|pages=19–26|doi=10.1016/S0895-4356(98)00138-3|pmid=9973070}}</ref>它还对主动对照等效试验的样本量产生重要影响，并且在理论上有助于'''<font color="#ff8000"> 亚组分析 Subgroup analysis </font>'''和'''<font color="#ff8000"> 中期分析 Interim analysis </font>'''。 <ref name=":6" />

在'''<font color="#ff8000"> 临床试验 Clinical trials </font>'''中，根据患者的社会和个人背景或与研究相关的任何因素对患者进行分层，以匹配整个患者群体中的每个组。 这样做的目的是建立临床/预后因素（prognostic factor）的平衡，因为如果研究设计不平衡，试验将不会产生有效的结果。<ref>{{Cite book|last1=Polit|first1=DF|title=Nursing Research: Generating and Assessing Evidence for Nursing Practice, 9th ed.|last2=Beck|first2=CT|publisher=Lippincott Williams & Wilkins.|year=2012|location=Philadelphia, USA: Wolters Klower Health}}</ref>  分层随机化的步骤非常重要，因为它试图确保没有偏见、有意或无意地影响所研究患者样本的代表性。 <ref>{{Cite web|url=https://www.omixon.com/patient-stratification-in-clinical-trials/|title=Patient Stratification in Clinical Trials|date=2014-12-01|website=Omixon {{!}} NGS for HLA|language=en-US|access-date=2020-04-26}}</ref>  它增加了研究能力，尤其是在小型临床试验中（n<400），因为这些已知的临床特征分层被认为会影响干预的结果。<ref>{{Cite web|url=https://www.statisticshowto.com/stratified-randomization/|title=Stratified Randomization in Clinical Trials|last=Stephanie|date=2016-05-20|website=Statistics How To|language=en-US|access-date=2020-04-26}}</ref>它有助于防止在临床研究中受到高度重视的 '''<font color="#ff8000"> I 型错误 Type I error </font>'''的发生。 <ref name=":6">{{Cite journal|last=Kernan|first=W|date=Jan 1999|title=Stratified Randomization for Clinical Trials|journal=Journal of Clinical Epidemiology|volume=52|issue=1|pages=19–26|doi=10.1016/S0895-4356(98)00138-3|pmid=9973070}}</ref>它还对主动对照等效试验的样本量产生重要影响，并且在理论上有助于'''<font color="#ff8000"> 亚组分析 Subgroup analysis </font>'''和'''<font color="#ff8000"> 中期分析 Interim analysis </font>'''。 <ref name=":6" />

==Advantage==

== Advantage ==

Category:Sampling techniques

# Stratified randomization can accurately reflect the outcomes of the general population since influential factors are applied to stratify the entire samples and balance the samples' vital characteristics among treatment groups. For instance, applying stratified randomization to make a sample of 100 from the population can guarantee the balance of males and females in each treatment group, while using simple randomization might result in only 20 males in one group and 80 males in another group.<ref name=":0" />

 

# Stratified randomization makes a smaller error than other sampling methods such as [[cluster sampling]], simple random sampling, and [[systematic sampling]] or [http://dissertation.laerd.com/non-probability-sampling.php non-probability methods] since measurements within strata could be made to have a lower [[standard deviation]]. Randomizing divided strata are more manageable and cheaper in some cases than simply randomizing general samples.<ref name=":1" />

# It is easier for a team to be trained to stratify a sample because of the exactness of the nature of stratified randomization.<ref name=":0" />

 

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# Sometimes stratified randomization is desirable to have estimates of population parameters for groups within the population.<ref name=":1" />

<small>This page was moved from [[wikipedia:en:Stratified randomization]]. Its edit history can be viewed at [[分层随机试验/edithistory]]</small></noinclude>

 

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