Search results for "Univariate"

Calibrating Expert Assessments Using Hierarchical Gaussian Process Models

2020

Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…

Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach

2021

In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator spe…

Managing for resilience: an information theory-based approach to assessing ecosystems

2016

Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications. We illustrate the utility of an information theory-based index for assessing ecosystem dynamics. Trends in this inde…

Prediction of unfavorable outcomes in West Nile virus neuroinvasive infection - Result of a multinational ID-IRI study

2019

Background: WNV causes 1.4% of all central nervous system infections and is the most common cause of epidemic neuro-invasive disease in humans. Objectives: Our main objective was to investigate retrospectively West Nile virus neuroinvasive disease (WNND) cases hospitalized during 2010–2017 and identified factors that can influence prognosis. Study design: We documented the demographic, epidemiologic, clinical and laboratory data of WNND and identified factors that can influence prognosis. The data were recruited through Infectious Diseases International Research Initiative (ID-IRI), which serves as a network for clinical researches. Results: We investigated 165 patients with WNND in 10 coun…

Fourier transform infrared analysis of commercial formulations for Varroa treatment

2017

A comparative study has been carried out between univariate and multivariate calibration strategies for the simultaneous determination of camphor, thymol, menthol and eucalyptol in commercial formulations used for Varroa treatment. Absorbance peak heights of the transmission mid-infrared (MIR) spectra of individual monoterpenes, prepared in dichloromethane, were measured at 1737, 1151, 1022 and 980 cm−1 (corrected with a base-line at 1933 cm−1) for camphor, thymol, menthol and eucalyptol, respectively. Data were processed using the proportional equations approach in univariate mode. For multivariate calibration, partial least squares (PLS) regression based on a classical 42 design for stand…

Transthyretin familial amyloid polyneuropathy (TTR‐FAP): Parameters for early diagnosis

2017

Abstract Background Familial transthyretin amyloidosis is a life‐threatening disease presenting with sensorimotor and autonomic polyneuropathy. Delayed diagnosis has a detrimental effect on treatment and prognosis. To facilitate diagnosis, we analyzed data patterns of patients with transthyretin familial amyloid polyneuropathy (TTR‐FAP) and compared them to polyneuropathies of different etiology for clinical and electrophysiological discriminators. Methods Twenty‐four patients with TTR‐FAP and 48 patients with diabetic polyneuropathy (dPNP) were investigated (neurological impairment score NIS; neurological disability score NDS) in a cross‐sectional design. Both groups were matched for gende…

Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling

2016

Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on …

2020

Background Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects. Results We systematically evaluated the performance of univariate ANOVA, Welch’s ANOVA and linear mixed effects models …

Factors influencing the development of visceral metastasis of breast cancer: A retrospective multi-center study.

2017

Abstract Purpose Visceral metastasis of breast cancer (BC) is an alarming development and correlates with poor median overall survival. The purpose of this retrospective study is to examine the risk factors for developing visceral metastasis by considering tumor biology and patient characteristics. Methods Using the BRENDA database, the risk factors such as histological and intrinsic subtypes of BC, age at primary diagnosis, grading, nodal status, tumor size and year of primary diagnosis were examined in univariate and multivariate analysis. Categorical variables were compared by using χ2 tests. Furthermore, multivariate Cox proportional hazards regression models, Kaplan–Meier product-limit…

Prognostic Nutritional Index as an independent prognostic factor in locoregionally advanced squamous cell head and neck cancer.

2018

Background: Locally advanced head and neck squamous cell carcinoma (LAHNSCC) is a heterogeneous disease in which better predictive and prognostic factors are needed. Apart from TNM stage, both systemic inflammation and poor nutritional status have a negative impact on survival. Methods: We retrospectively analysed two independent cohorts of a total of 145 patients with LAHNSCC treated with induction chemotherapy followed by concurrent chemoradiotherapy at two different academic institutions. Full clinical data, including the Prognostic Nutritional Index (PNI), neutrophil to lymphocyte ratio and derived neutrophil to lymphocyte ratio, were analysed in a training cohort of 50 patients. Receiv…