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第148行： − + − 分层随机化的优点包括：+ − 分层随机化可以准确反映一般人群的结果，因为应用影响因素对整个样本进行分层并平衡样本在治疗组之间的重要特征。例如，采用分层随机化从人群中抽取 100 名样本可以保证每个治疗组的男女平衡，而使用简单随机化可能会导致一组只有 20 名男性，而另一组有 80 名男性。 [7] ]+ − 分层随机化比其他抽样方法（例如整群抽样、简单随机抽样和系统抽样或非概率方法）的误差更小，因为可以使分层内的测量具有较低的标准偏差。在某些情况下，将分割的分层随机化比简单地随机化一般样本更易于管理且成本更低。 [11]+ − 由于分层随机化性质的精确性，团队更容易接受培训以对样本进行分层。 [7]+ − 由于这种方法的统计准确性，研究人员可以通过分析较小的样本量来获得非常有用的结果。+ − 这种抽样技术涵盖了广泛的人口，因为已经对地层划分进行了完整的充电。+ − 有时需要分层随机化来估计人口中各组的人口参数。 [11]+ − 坏处+ + +
→Advantage
# 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 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" />
# 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" />
优势
==优势 Advantage==
分层随机试验的优点包括：
#分层随机试验可以准确反映一般人群的结果，因为应用影响因素对整个样本进行分层并平衡样本在治疗组之间的重要特征。例如，采用分层随机化从人群中抽取 100 名样本可以保证每个治疗组的男女平衡，而使用简单随机化可能会导致一组只有 20 名男性，而另一组有 80 名男性。<ref name=":0" />
#分层随机试验比其他抽样方法（例如'''<font color="#ff8000"> 整群抽样 Cluster sampling </font>'''、简单随机抽样 和'''<font color="#ff8000"> 系统抽样 Systematic sampling </font>'''或'''<font color="#ff8000"> 非概率方法 Non-probability methods </font>'''）的误差更小，因为可以使分层内的测量具有较低的标准差。在某些情况下，将分割的分层随机试验比简单地随机试验一般样本更易于管理且成本更低。<ref name=":1" />
#由于分层随机试验本质的精确性，团队更容易接受分层样本的训练。
#由于这种方法的统计准确性，研究人员可以通过分析小样本得到非常有用的结果。
#'''<font color="#32cd32">这种抽样技术涵盖了广泛的总体，因为已经对分层划分进行了完整的 charge。 This sampling technique covers a wide range of population since complete charge over the strata division has been made.</font>'''
#有时需要分层随机试验来估计总体中各组的总体参数。<ref name=":1" />
==缺点 Disadvantage ==
分层随机化的限制包括：
分层随机化的限制包括：