1,720,967 research outputs found
Unconditional exact tests for the difference of binomial probabilities-contrasted and compared
No full textVarious exact tests for showing a difference between two treatments or the non-inferiority (therapeutic equivalence) based on the difference of two binomial proportions are compared. It is found that a frequently used test has to be applied with great caution due to its numerical instability. Furthermore, a test based on the score statistic can be recommended as a good compromise between a simple and powerful procedure. Finally, a likelihood ratio based exact test is introduced, which slightly outperforms all other tests from the literature with respect to power. The issue of sample size determination is briefly addressed. All methods are illustrated with help of an example where two antihelmintic agents are compared. (C) 2003 Elsevier B.V. All rights reserved
On Hadamard differentiability in k-sample semiparametric models—with applications to the assessment of structural relationships
No full textAbstractSemiparametric models to describe the functional relationship between k groups of observations are broadly applied in statistical analysis, ranging from nonparametric ANOVA to proportional hazard (ph) rate models in survival analysis. In this paper we deal with the empirical assessment of the validity of such a model, which will be denoted as a “structural relationship model”. To this end Hadamard differentiability of a suitable goodness-of-fit measure in the k-sample case is proved. This yields asymptotic limit laws which are applied to construct tests for various semiparametric models, including the Cox ph model. Two types of asymptotics are obtained, first when the hypothesis of the semiparametric model under investigation holds true, and second for the case when a fixed alternative is present. The latter result can be used to validate the presence of a semiparametric model instead of simply checking the null hypothesis “the model holds true”. Finally, various bootstrap approximations are numerically investigated and a data example is analyzed
Non-parametric assessment of non-inferiority with censored data
No full textWe suggest non-parametric tests for showing non-inferiority of a new treatment compared to a standard therapy when data are censored. To this end the difference and the odds ratio curves of the entire survivor functions over a certain time period are considered. Two asymptotic approaches for solving these testing problems are investigated, which are based on bootstrap approximations. The performance of the test procedures is investigated in a simulation study, and some guidance on which test to use in specific situations is derived. The proposed methods are applied to a trial in which two thrombolytic agents for the treatment on acute myocardial infarction were compared, and to a study on irradiation therapies for advanced non-small-cell lung cancer. Non-inferiority over a large time period of the study can be shown in both cases. Copyright (c) 2005 John Wiley & Sons, Ltd
A nonparametric test for similarity of marginals - With applications to the assessment of population bioequivalence
No full textIn this paper we suggest a completely nonparametric test for the assessment of similar marginals of a multivariate distribution function. This test is based on the asymptotic normality of Mallows distance between marginals. It is also shown that the n out of n bootstrap is weakly consistent, thus providing a theoretical justification to the work in Czado, C. and Munk, A. [2001. Bootstrap methods for the nonparametric assessment of population bioequivalence and similarity of distributions. J. Statist. Comput. Simulation 68, 243-280]. The test is extended to cross-over trials and is applied to the problem of population bioequivalence, where two formulations of a drug are shown to be similar up to a tolerable limit. This approach was investigated in small samples using bootstrap techniques in Czado, C., Munk, A. [2001. Bootstrap methods for the nonparametric assessment of population bioequivalence and similarity of distributions. J. Statist. Comput. Simulation 68, 243-280], showing that the bias corrected and accelerated bootstrap yields a very accurate and powerful finite sample correction. A data example is discussed. (c) 2006 Elsevier B.V. All rights reserved
Testing noninferiority in three-armed clinical trials based on likelihood ratio statistics
No full textClinical noninferiority trials with at least three groups have received much attention recently, perhaps due to the fact that regulatory agencies often require that a placebo group be evaluated along with a new experimental drug and an active control. The authors discuss likelihood ratio tests for binary endpoints and various noninferiority hypotheses. They find that, depending on the particular hypothesis, the test reduces asymptotically either to the intersection-union test or to a test which follows asymptotically a mixture of generalized chi-squared distributions. They investigate the performance of this asymptotic test and provide an exact modification. They show that this test considerably outperforms multiple testing methods such as the Bonferroni adjustment with respect to power. They illustrate their methods with a cancer study to compare antiemetic agents. Finally, they discuss the extension of the results to other settings, such as Gaussian endpoints
Vergleich zweier Messmethoden mit einem Goldstandard am Beispiel der 20-MHz-Sonographie und der klinischen Palpation zur Dickenbestimmung von pigmentierten Tumoren der Haut
No full textAim: This paper focuses on different statistical methods for comparing two measurement methods with an additionally available gold standard. A given data example is used as the basis of the calculations. Method: We provide a complementary statistical analysis of a study presented by Hoffmann et al. on sonometric and palpatory measurements of the size of pigmented skin tumours in 681 patients. Results: For comparing two measurement methods with respect to a gold standard, several statistical parameters assessing one measurement method can be used. In addition, there are further descriptive and some inference-statistical methods available. Conclusion: If there is a suitable categorization of the measurements, the comparison of the methods should be performed using the positive predictive values and kappa coefficients as descriptive measures. Moreover, the McNemar test can be used for comparing the differential accuracy of allocation. When investigating continuous measurements, a comparison using mere correlation analyses can lead to false conclusions. Therefore, we recommend the direct analysis of the individual measurement errors by means of numerical and graphical representations. The absolute values of the measurement errors can be compared using the sign test for paired samples
On Difference-Based Variance Estimation in Nonparametric Regression When the Covariate is High Dimensional
No full textWe consider the problem of estimating the noise variance in homoscedastic nonparametric regression models. For low dimensional covariates t is an element of R-d, d=1, 2, difference-based estimators have been investigated in a series of papers. For a given length of such an estimator, difference schemes which minimize the asymptotic mean-squared error can be computed for d=1 and d=2. However, from numerical studies it is known that for finite sample sizes the performance of these estimators may be deficient owing to a large finite sample bias. We provide theoretical support for these findings. In particular, we show that with increasing dimension d this becomes more drastic. If dgreater than or equal to4, these estimators even fail to be consistent. A different class of estimators is discussed which allow better control of the bias and remain consistent when dgreater than or equal to4. These estimators are compared numerically with kernel-type estimators (which are asymptotically efficient), and some guidance is given about when their use becomes necessary
Assessing structural relationships between distributions - a quantile process approach based on Mallows distance
No full textWe suggest diagnostic tools for the assessment of shape similarity of distributions, i.e. whether several distributions are equal up to a pre-specified semiparametric deviation, such as a simple shift in location or a scale deviation. This will be called a structural relationship between distributions, and it is of importance, for instance, in an initial analysis within the (nonparametric) analysis of variance. Our approach is based on a modification of a trimmed version of Mallows distance between distribution functions. Asymptotic theory for the corresponding test statistics is provided and a bootstrap limit theorem is shown. In particular, the case of dependent samples is covered as well. A simulation study reveals the bias corrected and accelerated bootstrap as an adequate method for the assessment of shape similar distributions. A medical application is discussed
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
