When analysing and presenting results ofrandomised clinical trials, trialists rarely report if or how underlying statisticalassumptions were validated. To avoid data-driven biased trial results, it should ...
This paper focuses on the problem of testing the null hypothesis that the variance functions of two populations are equal versus one-sided alternatives under a general nonparametric heteroscedastic regression ...
We analyze the utility of multiscale supervised classification algorithms for object detection and extraction from laser scanning or photogrammetric point clouds. Only the geometric information (the point ...
The evaluation of mediastinal lymph nodes is critical for the correct staging of patients with lung cancer (LC). Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally ...
Background The currently known breast cancer-associated single nucleotide polymorphisms (SNPs) are presently not used to guide clinical management. We explored whether a genetic test that incorporates ...
Purpose: Biallelic pathogenic variants in the mismatch repair (MMR) genes cause a recessive childhood cancer predisposition syndrome known as constitutional mismatch repair deficiency (CMMRD). Family members ...
We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (J Am Stat Assoc 72(358):320–338, 1977)’s work, but it is able ...
When the same data are used to fit a model and estimate its predictive performance, this estimate may be optimistic, and its correction is required. The aim of this work is to compare the behaviour of ...
Weight management strategies during pregnancy reduce child cardiometabolic risk. However, because maternal weight has an overall positive correlation with offspring bone mass, pregnancy weight management ...
Multivariate response data often arise in practice and they are frequently subject to missingness. Under this circumstance, the standard sufficient dimension reduction (SDR) methods cannot be used directly. ...
Background: Current HIV treatment guidelines recommend antiretroviral treatment (ART) initiation for all HIV-infected individuals regardless of CD4 count. This study evaluates the immunological and virological ...
Introduction: Osteoarthritis is the osteoarticular disease with the highest prevalence worldwide. In industrialized countries, 80% of the population > 65 years suffers from it. Objectives: To determine ...
Objective: To find autoantibodies (AAbs) in serum that could be useful to predict incidence of radiographic knee osteoarthritis (KOA). Design: A Nucleic-acid Programmable Protein Arrays (NAPPA) platform ...
In this paper, we consider a general regression model where missing data occur in the response and in the covariates. Our aim is to estimate the marginal distribution function and a marginal functional, ...
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 ...
In this paper we present a method to forecast pollution episodes using measurements of the pollutant concentration along time. Specifically, we use a backfitting algorithm with local polynomial kernel ...
Several aquatic living resources are overexploited. An example of this is a barnacle fishery, which is a commercial species that commands high prices in the market. We feel that not enough is known about ...
Background
The value of carotid intervention is predicated on long-term survival for patients to derive a stroke prevention benefit. Randomized trials report no significant difference in survival after ...
Objective:
To describe the long-term reintervention rate after endovascular abdominal aortic aneurysm repair (EVR), and identify factors predicting reintervention.
Summary of Background Data:
EVR is ...
Two‐stage instrumental variable methods are commonly used for estimating average causal effects in the presence of an unmeasured confounder. In the context of the proportional hazard Cox regression models, ...
In this research, an algorithm is presented for predicting the remaining useful life (RUL) of aircraft engines from a set of predictor variables measured by several sensors located in the engine. RUL prediction ...
The paper first introduces a new two-parameter continuous probability distribution
with bounded support from the extended exponential-geometric distribution. Closed-
form expressions are given for the ...
The problem of testing for the parametric form of the conditional variance is considered
in a fully nonparametric regression model. A test statistic based on a weighted
L2-distance between the empirical ...
A test for the equality of error distributions in two nonparametric regression models is proposed. The test statistic is based on comparing the empirical characteristic functions of the residuals calculated ...
BACKGROUND: The optimal blood management after cardiac surgery remains controversial. Moreover, blood transfusions may have an impact on long-term outcomes.
OBJECTIVE: The aim of this study is to characterize ...
Objective
Use logistic regression to determine a mathematical model which is able to predict injuries in aerobic gymnastics (AG) athletes, according to certain anthropometric characteristics.
Subjects ...
Aims and objectives: To analyse quality of life and satisfaction after immediate breast reconstruction due to cancer and its determining factors.
Background: Studying breast reconstruction is important ...
Enriching existing predictive models with new biomolecular markers is an important task in the new multi-omic era. Clinical studies increasingly include new sets of omic measurements which may prove their ...
We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (J Am Stat Assoc 72(358):320–338, 1977)’s work, but it is able ...
Lamin A/C gene (LMNA)-related familial dilated cardiomyopathy (fDCM) is an aggressive heart disease that often leads to transplantation and sudden death. The aim of our study was to evaluate the circulating ...
The purpose of this paper is two fold. First, we investigate estimation for varying coefficient partially linear models in which covariates in the nonparametric part are measured with errors. As there ...
In this paper, we study the linear quantile regression model when response data are missing at random. Based on the inverse probability weight method, we establish an estimation equation on quantile regression ...
Based on the inverse probability weight method, we, in this article, construct the empirical likelihood (EL) and penalized empirical likelihood (PEL) ratios of the parameter in the linear quantile regression ...
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 ...
Building prediction models based on complex omics datasets such as transcriptomics, proteomics, metabolomics remains a challenge in bioinformatics and biostatistics. Regularized regression techniques are ...
Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most ...
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 ...
Doubly truncated data arise when event times are observed only if they fall within subject-specific, possibly random, intervals. While non-parametric methods for survivor function estimation using doubly ...
In this paper, we focus on the partially linear varying-coefficient quantile regression model when the data are right censored and the censoring indicator is missing at random. Based on the calibration ...
This paper proposes a method to estimate leaf water content from reflectance in four commercial vineyard varieties by estimating the local maxima of a distance correlation function. First, it applies four ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...
Enrichment of predictive models with new biomolecular markers is an important task in high-dimensional omic applications. Increasingly, clinical studies include several sets of such omics markers available ...
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 ...
When developing prediction models for application in clinical practice, health practitioners usually categorise clinical variables that are continuous in nature. Although categorisation is not regarded ...
This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.
Data from 2409 COPD patients of ...
In this work, some properties of the L2-deviations of the Nadaraya-Watson variogram estimators are analyzed, for both the anisotropic and the isotropic settings. Their convergence in distribution is established, ...
While evidence for lung cancer screening implementation in Europe is awaited, Rapid Diagnostic Units have been established in many hospitals to accelerate the early diagnosis of lung cancer. We seek to ...
The Cox proportionalhazards model is the most widely used survival predictionmodel for analysing time-to-event data. To measure the discrimination ability of a survival model the concordance probability ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...