... its standard probabilistic interpretation. The analogy between the hypothesis tests and the usual diagnostic process (both involve a decision-making) is used to point out some limitations in the probabilistic ...
... used for initiation were recorded. A statistical analysis was performed using SPSS version 19 software. Categorical and continuous variables were compared by the specific statistical tests, and a logistic ...
... assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider ...
... of the test. An alternative global test based on the P-values derived from permutation tests is also proposed. A simulation study to investigate the finite sample properties of the proposed tests is carried ...
Goodness–of–fit tests for quantile regression models, in the presence of missing observations in the response variable, are introduced and analyzed in this paper. The different proposals are based on the ...
We consider a goodness-of-fit test for certain parametrizations of conditionally heteroscedastic time series with unobserved components. Our test is quite general in that it can be employed to validate ...
The one-parameter Bell family of distributions, introduced by Castellares et al. (Appl Math Model 56:172–185, 2018), is useful for modeling count data. This paper proposes and studies a goodness-of-fit ...
Next‐generation sequencing (NGS) experiments are often performed in biomedical research nowadays, leading to methodological challenges related to the high‐dimensional and complex nature of the recorded ...
We generalize a recent class of tests for univariate normality that are based on the empirical moment generating function to the multivariate setting, thus obtaining a class of affine invariant, consistent ...
... invariant, consistent and easy-to-use goodness-of-fit tests for normality. The test statistics are suitably weighted L2-statistics, and we provide their asymptotic behavior both for i.i.d. observations ...
A class of tests for testing independence whose test statistic is an -norm of the difference between the joint empirical characteristic function and the product of the marginal empirical characteristic ...
... playing situations, attacks outcome, origin of shots and technical execution of shots. Univariate (ANOVA, Kruskal-Wallis and Generalized Linear Model tests) and multivariate (Discriminant) analyses were ...
... ability of continuous-outcome diagnostic tests. It has been acknowledged that several factors (e.g., subject-specific characteristics, such as age and/or gender) can affect the test's accuracy beyond diseas ...
... option for large sample sizes and values of d not near to ±1 is the classic method of Peskun; and (4) in the particular case of the superiority and inferiority tests, the optimal method is the classic ...
This article proposes a new general methodology for constructing nonparametric and semiparametric Asymptotically Distribution-Free (ADF) tests for semiparametric hypotheses in regression models for possibly ...
... better results in the functional tests than the rest of the former workers, having a lower drop in the Forced Vital Capacity (FVC) percentage with a minor statistical relevance (p= 0,02), besides the small ...
Background: Colorectal cancer is the fourth cause of cancer-related deaths worldwide, though detection at early stages associates with good prognosis. Thus, there is a clear demand for novel non-invasive ...
... widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, ...
Several procedures have been proposed for testing goodness-of-fit to the error distribution in nonparametric regression models. The null distribution of the associated test statistics is usually approximated ...
Several procedures have been proposed for testing the equality of error distributions in two or more nonparametric regression models. Here we deal with methods based on comparing estimators of the cumulative ...
... which provides the basis for addressing practical problems, such as the construction of goodness of fit tests for the variogram and, therefore, for modeling the spatial dependence. However, the development ...
Goodness-of-fit tests for the innovation distribution in GARCH models based on measuring deviations between the empirical characteristic function of the residuals and the characteristic function under ...
... methodologies have been developed in order to perform meta-analytic studies of diagnostic tests for both fixed- and random-effects models. From a parametric point of view, these techniques often compute ...
A class of tests for the two-sample problem whose test statistic is an L2 norm of the difference of the empirical characteristic functions of the samples is considered. The null distribution can be estimated ...
A class of tests for the two-sample problem for count data whose test statistic is an
L2-norm of the difference between the empirical probability generating functions associated with each sample is considered. ...
Tests are proposed for the assumption that the conditional distribution of a multivariate GARCH process is elliptic. These tests are of Kolmogorov–Smirnov and Cramér–von Mises-type and make use of the ...
... of shots. Univariate analyses (ANOVA, Kruskal-Wallis and generalised linear model (GLM) tests) were conducted to identify differences in the offensive variables between “strong”, “medium” or “weak” teams’ ...
... of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy needs to be also assessed. ...
... As a prerequisite, some asymptotic properties of the minimum integrated squared error estimators are studied. From these properties, consistent tests for model selection based on CFs are given for separate, ...
... of the test statistic is studied under the null hypothesis and under root
local alternatives. A Monte Carlo study is performed to compare the finite sample behaviour of the proposed tests with the classical ...
This paper analyses the behaviour of the goodness-of-fit tests for regression models. To this end, it uses statistics based on an estimation of the integrated regression function with missing observations ...
... reject the given null hypothesis, while controlling for the multiplicity of tests. The main properties of the adjusted p-values are investigated. In particular, we show that they are a subset of the original ...
... when the tests are correlated in blocks.
In this paper we investigate for the first time the power, the FDR and the conservativeness of BB-SGoF in an intensive Monte Carlo simulation study. Important ...
A class of goodness-of-fit tests of the Cramer-von Mises type is considered. More specifically, the test statistic of each test is an L-2-norm of the difference between the empirical characteristic function ...
A class of goodness-of-fit tests whose test statistic is an L-2 norm of the difference of the empirical characteristic function of the sample and a parametric estimate of the characteristic function in ...
... the classical false discovery rate (FDR) and family-wise error rate (FWER) based methods in certain situations, particularly when the number of tests is large. This package includes Binomial and Conservative ...
... but might behave badly when the assumed parametric model is far off. In this paper we introduce several goodness-of-fit tests for the parametric model.
The proposed tests are investigated through simulations. ...
In a recent paper (de Uña-Álvarez, 2012, Statistical Applications in Genetics and Molecular Biology Vol. 11, Iss. 3, Article 14) a correction of SGoF multitesting method for possibly dependent tests was ...
In this paper, the problem of bandwidth choice in smooth k-sample tests is considered. Three different bootstrap methods are discussed and implemented. All the methods persecute the bandwidth leading to ...
In this paper the problem of comparing k density functions from survival data is considered. Two non-parametric tests based on (two different) generalizations of the L1 measure are adapted to the censored ...
In this paper a correction of SGoF multitesting method for dependent tests is introduced.
The correction is based in the beta-binomial model, and therefore the new method is called Beta-Binomial SGoF ...
... is paid to the huge dimension problem in which the number of tests goes to infinity. Formulae for the power and the rate of false discoveries/non-discoveries of SGoF are given, so the role of the gamma-parameter ...
When working with high-dimensional biological data the so-called multiple hypothesis testing problem emerges. That is, when many separate tests are performed, several will be significant by chance provoking ...
... coefficient or Akaike Information Criterion) and taking into account the computational cost. Additionally, bootstrap resampling techniques are used to implement tests capable of detecting whether significant ...