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Some group sequential testing method...

Feng, Huaibao.

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Some group sequential testing methods in clinical trials.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Some group sequential testing methods in clinical trials./
作者:	Feng, Huaibao.
面頁冊數:	112 p.
附註:	Adviser: Jun Shao.
Contained By:	Dissertation Abstracts International69-05B.
標題:	Biology, Biostatistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3314181
ISBN:	9780549632641

Some group sequential testing methods in clinical trials.
Feng, Huaibao.

Some group sequential testing methods in clinical trials. - 112 p.

Adviser: Jun Shao.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2008.

In clinical research and development, group sequential testing methods have been widely used for ethical, administrative and economic considerations. In this dissertation, we first consider the group sequential t-test procedure for clinical trials with small sample sizes across stages. As we know, normal approximation of test statistic is only accurate with large sample size. We propose to approximate the distribution of the test statistic by t-distribution. The resulted critical values and sample sizes under this situation are considered.

ISBN: 9780549632641Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Some group sequential testing methods in clinical trials.
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245 1 0 $a Some group sequential testing methods in clinical trials.
300 $a 112 p.
500 $a Adviser: Jun Shao.
500 $a Source: Dissertation Abstracts International, Volume: 69-05, Section: B, page: 2703.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2008.
520 $a In clinical research and development, group sequential testing methods have been widely used for ethical, administrative and economic considerations. In this dissertation, we first consider the group sequential t-test procedure for clinical trials with small sample sizes across stages. As we know, normal approximation of test statistic is only accurate with large sample size. We propose to approximate the distribution of the test statistic by t-distribution. The resulted critical values and sample sizes under this situation are considered.
520 $a In the classical group sequential testing procedure, a typical assumption is that the patient population is homogeneous across the trial. After each interim analysis, however, it is not uncommon to adjust/modify the trial procedure or the study design for various reasons. As a result, the actual patient population in the later stages of a trial could deviate from the original population. To deal with this problem, we consider population changes that are related to some covariates of an on-going trial. First, we define the patient population in the first stage as the target population and propose a test statistic/procedure to test the treatment effect on this target population. Second, we want to test the treatment effect on the overall patient population by adjusting for the effect of changing covariate(s). We impose fixed effect on the changing covariate, and propose the group sequential analysis of covariance (ANCOVA) testing procedures when the changing covariate is continuous; we impose random effect on the changing covariate, and propose the group sequential analysis of variance (ANOVA) testing procedures when the changing covariate is categorical.
520 $a After that, we also briefly consider the problem of switching from superiority hypothesis to non-inferiority hypothesis in the group sequential testing scheme. Two such group sequential testing rules are proposed. Numerical methods for computing the corresponding critical values are studied. Simulation studies were carried out to evaluate the properties of these two test rules.
590 $a School code: 0262.
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