Not all voxels are created equal: reducing estimation bias in regional NODDI metrics using tissue-weighted means

10.1101/2021.06.29.450089 ◽

2021 ◽

Author(s):

Christopher S Parker ◽

Thomas Veale ◽

Martina Bocchetta ◽

Catherine F Slattery ◽

Ian B Malone ◽

...

Keyword(s):

Conventional Method ◽

Estimation Bias ◽

Weighted Mean ◽

Partial Volume ◽

Neuronal Communication ◽

Promising Tool ◽

Weighted Means ◽

The Mean ◽

Biased Estimates ◽

Tissue Fraction

Neurite orientation dispersion and density imaging (NODDI) estimates microstructural properties of neurites relating to their organisation and processing capacity that are essential for effective neuronal communication. Descriptive statistics of NODDI tissue metrics are commonly analysed in regions-of-interest (ROI) to identify brain behaviour associations. Here, the conventional method to calculate the ROI mean weights all voxels equally. However, this produces biased estimates in the presence of CSF partial volume. This study introduces the tissue-weighted mean, which calculates the mean NODDI metric across the tissue within an ROI, utilising the tissue fraction estimate from NODDI to reduce estimation bias. We demonstrate the proposed mean in a study of white matter abnormalities in young onset Alzheimer's disease (YOAD). Results show the conventional method induces significant bias that correlates with CSF partial volume, primarily affecting periventricular regions and more so in YOAD subjects than in healthy controls. The tissue-weighted mean robustly identified disease-related differences in ROIs such as the fornix (p<0.05, Bonferroni corrected), some of which were absent using the conventional mean. The tissue-weighted mean may generate new insight into microstructural disease-related effects in regions typically confounded by partial volume, representing a promising tool for the study of microstructural correlates of aging and neurodegenerative diseases.

Download Full-text

Parameter estimation, bias correction and uncertainty quantification in the Vasicek credit portfolio model

The Journal of Risk ◽

10.21314/jor.2020.429 ◽

2020 ◽

Author(s):

Marius Pfeuffer ◽

Maximilian Nagl ◽

Matthias Fischer ◽

Daniel Rösch

Keyword(s):

Parameter Estimation ◽

Uncertainty Quantification ◽

Bias Correction ◽

Estimation Bias ◽

Credit Portfolio ◽

Credit Portfolio Model

Download Full-text

Estimation Bias and Monitoring in Clean Development Mechanism Projects

SSRN Electronic Journal ◽

10.2139/ssrn.2597443 ◽

2015 ◽

Cited By ~ 1

Author(s):

Hui Chen ◽

Peter Letmathe ◽

Naomi S. Soderstrom

Keyword(s):

Clean Development Mechanism ◽

Estimation Bias ◽

Development Mechanism

Download Full-text

A random effects population dynamics model based on proportions-at-age and removal data for estimating total mortality

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f2012-103 ◽

2012 ◽

Vol 69 (11) ◽

pp. 1881-1893 ◽

Cited By ~ 6

Author(s):

Verena M. Trenkel ◽

Mark V. Bravington ◽

Pascal Lorance

Keyword(s):

Population Dynamics ◽

Random Effects ◽

Fixed Effects ◽

Random Effect ◽

Total Mortality ◽

Estimation Bias ◽

Effective Sample Size ◽

Dynamics Model ◽

Population Dynamics Model ◽

Study Parameter

Catch curves are widely used to estimate total mortality for exploited marine populations. The usual population dynamics model assumes constant recruitment across years and constant total mortality. We extend this to include annual recruitment and annual total mortality. Recruitment is treated as an uncorrelated random effect, while total mortality is modelled by a random walk. Data requirements are minimal as only proportions-at-age and total catches are needed. We obtain the effective sample size for aggregated proportion-at-age data based on fitting Dirichlet-multinomial distributions to the raw sampling data. Parameter estimation is carried out by approximate likelihood. We use simulations to study parameter estimability and estimation bias of four model versions, including models treating mortality as fixed effects and misspecified models. All model versions were, in general, estimable, though for certain parameter values or replicate runs they were not. Relative estimation bias of final year total mortalities and depletion rates were lower for the proposed random effects model compared with the fixed effects version for total mortality. The model is demonstrated for the case of blue ling (Molva dypterygia) to the west of the British Isles for the period 1988 to 2011.

Download Full-text

Characterization of Deleterious Mutations in Outcrossing Populations

Genetics ◽

10.1093/genetics/150.2.945 ◽

1998 ◽

Vol 150 (2) ◽

pp. 945-956 ◽

Cited By ~ 4

Author(s):

Hong-Wen Deng

Keyword(s):

Genetic Variation ◽

Genetic Variance ◽

Estimation Bias ◽

Deleterious Mutations ◽

Environmental Variance ◽

Higher Power ◽

Sib Mating ◽

The Mean ◽

Simulation Results

Abstract Deng and Lynch recently proposed estimating the rate and effects of deleterious genomic mutations from changes in the mean and genetic variance of fitness upon selfing/outcrossing in outcrossing/highly selfing populations. The utility of our original estimation approach is limited in outcrossing populations, since selfing may not always be feasible. Here we extend the approach to any form of inbreeding in outcrossing populations. By simulations, the statistical properties of the estimation under a common form of inbreeding (sib mating) are investigated under a range of biologically plausible situations. The efficiencies of different degrees of inbreeding and two different experimental designs of estimation are also investigated. We found that estimation using the total genetic variation in the inbred generation is generally more efficient than employing the genetic variation among the mean of inbred families, and that higher degree of inbreeding employed in experiments yields higher power for estimation. The simulation results of the magnitude and direction of estimation bias under variable or epistatic mutation effects may provide a basis for accurate inferences of deleterious mutations. Simulations accounting for environmental variance of fitness suggest that, under full-sib mating, our extension can achieve reasonably well an estimation with sample sizes of only ∼2000-3000.

Download Full-text

Spatio-temporal expectile regression models

Statistical Modelling ◽

10.1177/1471082x19829945 ◽

2019 ◽

Vol 20 (4) ◽

pp. 386-409

Author(s):

Elmar Spiegel ◽

Thomas Kneib ◽

Fabian Otto-Sobotka

Keyword(s):

Tensor Product ◽

Least Squares Regression ◽

Expectile Regression ◽

Specific Distribution ◽

Weighted Means ◽

Temporal Models ◽

Error Terms ◽

Spatio Temporal ◽

Set Up ◽

Main Effects

Spatio-temporal models are becoming increasingly popular in recent regression research. However, they usually rely on the assumption of a specific parametric distribution for the response and/or homoscedastic error terms. In this article, we propose to apply semiparametric expectile regression to model spatio-temporal effects beyond the mean. Besides the removal of the assumption of a specific distribution and homoscedasticity, with expectile regression the whole distribution of the response can be estimated. For the use of expectiles, we interpret them as weighted means and estimate them by established tools of (penalized) least squares regression. The spatio-temporal effect is set up as an interaction between time and space either based on trivariate tensor product P-splines or the tensor product of a Gaussian Markov random field and a univariate P-spline. Importantly, the model can easily be split up into main effects and interactions to facilitate interpretation. The method is presented along the analysis of spatio-temporal variation of temperatures in Germany from 1980 to 2014.

Download Full-text

Weighted Means, Strict Ergodicity, and Uniform Distributions

Mathematical Notes ◽

10.1007/s11006-005-0132-x ◽

2005 ◽

Vol 78 (3-4) ◽

pp. 329-337 ◽

Cited By ~ 1

Author(s):

V. V. Kozlov

Keyword(s):

Uniform Distributions ◽

Weighted Means

Download Full-text

The role of vitamin D in metabolic disturbances in polycystic ovary syndrome: a systematic review

Acta Endocrinologica ◽

10.1530/eje-13-0617 ◽

2013 ◽

Vol 169 (6) ◽

pp. 853-865 ◽

Cited By ~ 57

Author(s):

Y H M Krul-Poel ◽

C Snackey ◽

Y Louwers ◽

P Lips ◽

C B Lambalk ◽

...

Keyword(s):

Systematic Review ◽

Vitamin D ◽

Clinical Trials ◽

Polycystic Ovary Syndrome ◽

Polycystic Ovary ◽

Vitamin D Status ◽

Regression Analyses ◽

Metabolic Disturbances ◽

Ovary Syndrome ◽

Weighted Means

ContextMetabolic disturbances, in particular, insulin resistance (IR) and dyslipidemia, are common in women suffering from polycystic ovary syndrome (PCOS). Evidence is accumulating that vitamin D status may contribute to the development of metabolic disturbances in PCOS.ObjectiveThe aim of this study was to carry out a systematic review addressing the association between vitamin D status, vitamin D receptor polymorphisms, and/or polymorphisms related to vitamin D metabolism and metabolic disturbances in women with PCOS.Design and methodsA systematic search of electronic databases was carried out up to January 2013 for observational studies and clinical trials in women suffering from PCOS with outcome measures that were related to vitamin D status. We conducted univariate and multivariate regression analyses of the weighted means to gain insights into the association between vitamin D, BMI, and IR based on existing literature.ResultsWe found 29 eligible trials with inconsistency in their results. One well-designed randomized controlled trial has been carried out until now. Univariate regression analyses of the weighted means revealed vitamin D to be a significant and independent predictor of IR in both PCOS and control women. The significance disappeared after adjustment for BMI in PCOS women.ConclusionsCurrent evidence suggests an inverse association between vitamin D status and metabolic disturbances in PCOS. Owing to the heterogeneity of the studies, it is hard to draw a definite conclusion. The causal relationship between vitamin D status and metabolic disturbances in PCOS remains to be determined in well-designed placebo-controlled randomized clinical trials.

Download Full-text