Sequential tests of multiple hypotheses controlling type I and II familywise error rates
نویسندگان
چکیده
منابع مشابه
Sequential Tests of Multiple Hypotheses Controlling Type I and II Familywise Error Rates.
This paper addresses the following general scenario: A scientist wishes to perform a battery of experiments, each generating a sequential stream of data, to investigate some phenomenon. The scientist would like to control the overall error rate in order to draw statistically-valid conclusions from each experiment, while being as efficient as possible. The between-stream data may differ in distr...
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We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together we call these conditions a "rejection principle for sequential tests," which we then apply to some existing sequential multiple testing procedures to give simplified unde...
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The idea of modifying, and potentially improving, classical multiple testing methods controlling the familywise error rate (FWER) via an estimate of the unknown number of true null hypotheses has been around for a long time without a formal answer to the question whether or not such adaptive methods ultimately maintain the strong control of FWER, until Finner and Gontscharuk (2009) and Guo (200...
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This work studies multiple hypothesis testing in the setting when we obtain data sequentially and may choose when to stop sampling. We summarize the notion of a sequential pvalue (one that can be continually updated and still maintain a type I error guarantee) and provide several examples from the literature. This tool allows us to convert fixedhorizon step-up or step-down multiple hypothesis t...
متن کاملType I and II error
Type I error A type I error occurs when one rejects the null hypothesis when it is true. The probability of a type I error is the level of significance of the test of hypothesis, and is denoted by *alpha*. Usually a one-tailed test of hypothesis is is used when one talks about type I error. Examples: If the cholesterol level of healthy men is normally distributed with a mean of 180 and a standa...
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ژورنال
عنوان ژورنال: Journal of Statistical Planning and Inference
سال: 2014
ISSN: 0378-3758
DOI: 10.1016/j.jspi.2014.05.010