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→缺点 Disadvantage
==缺点 Disadvantage ==
==缺点 Disadvantage ==
== Disadvantage ==
The limits of stratified randomization include:
# Stratified randomization firstly divides samples into several strata with reference to prognostic factors but there is possible that the samples are unable to be divided. In application, the significance of prognostic factors lacks strict approval in some cases, which could further result in bias. This is why the factors' potential for making effects to result should be checked before the factors are included in stratification. In some cases that the impact of factors on the outcome cannot be approved, unstratified randomization is suggested.<ref>{{Cite web|url=https://www.investopedia.com/ask/answers/041615/what-are-advantages-and-disadvantages-stratified-random-sampling.asp|title=Pros and Cons of Stratified Random Sampling|last=Murphy|first=Chris B.|date=Apr 13, 2019|website=Investopedia|language=en|access-date=2020-04-07}}</ref>
# The subgroup size is taken to be of the same importance if the data available cannot represent overall subgroup population. In some applications, subgroup size is decided with reference to the amount of data available instead of scaling sample sizes to subgroup size, which would introduce bias in the effects of factors. In some cases that data needs to be stratified by variances, subgroup variances differ significantly, making each subgroup sampling size proportional to the overall subgroup population cannot be guaranteed.<ref name=":2">{{Citation|last1=Glass|first1=Aenne|title=Potential Advantages and Disadvantages of Stratification in Methods of Randomization|date=2014|work=Springer Proceedings in Mathematics & Statistics|pages=239–246|publisher=Springer New York|isbn=978-1-4939-2103-4|last2=Kundt|first2=Guenther|doi=10.1007/978-1-4939-2104-1_23}}</ref>
# Stratified sampling can not be applied if the population cannot be completely assigned into strata, which would result in sample sizes proportional to sample available instead of overall subgroup population.<ref name=":0" />
# The process of assigning samples into subgroups could involve overlapping if subjects meet the inclusion standard of multiple strata, which could result in a misrepresentation of the population.<ref name=":2" />
分层随机化的限制包括：
分层随机化的限制包括：