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41.
Lili Tian Albert Vexler Li Yan Enrique F. Schisterman 《Journal of statistical planning and inference》2009
In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice. 相似文献
42.
Modified inference about the mean of the exponential distribution using moving extreme ranked set sampling 总被引:1,自引:1,他引:0
The maximum likelihood estimator (MLE) and the likelihood ratio test (LRT) will be considered for making inference about the
scale parameter of the exponential distribution in case of moving extreme ranked set sampling (MERSS). The MLE and LRT can
not be written in closed form. Therefore, a modification of the MLE using the technique suggested by Maharota and Nanda (Biometrika
61:601–606, 1974) will be considered and this modified estimator will be used to modify the LRT to get a test in closed form
for testing a simple hypothesis against one sided alternatives. The same idea will be used to modify the most powerful test
(MPT) for testing a simple hypothesis versus a simple hypothesis to get a test in closed form for testing a simple hypothesis
against one sided alternatives. Then it appears that the modified estimator is a good competitor of the MLE and the modified
tests are good competitors of the LRT using MERSS and simple random sampling (SRS). 相似文献
43.
44.
Alison Salloum Michael L. Sulkowski Erica Sirrine Eric A. Storch 《Child and Adolescent Social Work Journal》2009,26(3):259-273
Anxiety disorders are among the most common psychiatric disorders in children and adolescents. Most empirically supported
treatments (ESTs) for pediatric anxiety disorders include various cognitive-behavioral methods. Although demonstrated efficacious
in controlled and clinic settings, there are barriers to implementing these types of therapies in social work settings due
to beliefs about the usefulness of ESTs in community settings; limitations of treatment manuals; time constraints of implementing
ESTs; fidelity and flexibility of implementing ESTs; and limited training opportunities. This article provides an overview
of ESTs for childhood anxiety disorders, highlighting options for overcoming common barriers to implementing ESTs. Collaborative
multi-method approaches to advance implementation of ESTs in social work practice are suggested. 相似文献
45.
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47.
Zdeněk Hlávka Marie Hušková Claudia Kirch Simos G. Meintanis 《Econometric Reviews》2017,36(4):468-492
We develop testing procedures which detect if the observed time series is a martingale difference sequence. Furthermore, tests are developed that detect change–points in the conditional expectation of the series given its past. The test statistics are formulated following the approach of Fourier–type conditional expectations first proposed by Bierens (1982) and have the advantage of computational simplicity. The limit behavior of the test statistics is investigated under the null hypothesis as well as under alternatives. Since the asymptotic null distribution contains unknown parameters, a bootstrap procedure is proposed in order to actually perform the test. The performance of the bootstrap version of the test is compared in finite samples with other methods for the same problem. A real–data application is also included. 相似文献
48.
For ethical reasons, group sequential trials were introduced to allow trials to stop early in the event of extreme results. Endpoints in such trials are usually mortality or irreversible morbidity. For a given endpoint, the norm is to use a single test statistic and to use that same statistic for each analysis. This approach is risky because the test statistic has to be specified before the study is unblinded, and there is loss in power if the assumptions that ensure optimality for each analysis are not met. To minimize the risk of moderate to substantial loss in power due to a suboptimal choice of a statistic, a robust method was developed for nonsequential trials. The concept is analogous to diversification of financial investments to minimize risk. The method is based on combining P values from multiple test statistics for formal inference while controlling the type I error rate at its designated value.This article evaluates the performance of 2 P value combining methods for group sequential trials. The emphasis is on time to event trials although results from less complex trials are also included. The gain or loss in power with the combination method relative to a single statistic is asymmetric in its favor. Depending on the power of each individual test, the combination method can give more power than any single test or give power that is closer to the test with the most power. The versatility of the method is that it can combine P values from different test statistics for analysis at different times. The robustness of results suggests that inference from group sequential trials can be strengthened with the use of combined tests. 相似文献
49.
In this paper we provide three nonparametric tests of independence between continuous random variables based on the Bernstein copula distribution function and the Bernstein copula density function. The first test is constructed based on a Cramér-von Mises divergence-type functional based on the empirical Bernstein copula process. The two other tests are based on the Bernstein copula density and use Cramér-von Mises and Kullback–Leibler divergence-type functionals, respectively. Furthermore, we study the asymptotic null distribution of each of these test statistics. Finally, we consider a Monte Carlo experiment to investigate the performance of our tests. In particular we examine their size and power which we compare with those of the classical nonparametric tests that are based on the empirical distribution function. 相似文献
50.