Piero Quatto

Brain network connectivity assessed using graph theory in frontotemporal dementia.

Objective: To investigate whether brain functional network connectivity is disrupted in patients with the behavioral variant of frontotemporal dementia (bvFTD). Methods: Graph theoretical analysis was applied to resting state functional MRI data from 18 patients with probable bvFTD and 50 healthy individuals. Functional connectivity between 90 cortical and subcortical brain regions was estimated using bivariate correlation analysis and thresholded to construct a set of undirected graphs. Correlations between network properties and cognitive variables were tested. Results: Global topologic organization of the functional brain network in bvFTD was significantly disrupted as indicated by reduced mean network degree, clustering coefficient, and global efficiency and increased characteristic path length and assortativity relative to normal subjects. Compared to controls, bvFTD data showed retention of major “hub” regions in the medial parietal, temporal, and occipital lobes, but cortical hubs were not noted in the frontal lobes. Medial and dorsal frontal regions, left caudate nucleus, left insular cortices, and some regions of the temporal, parietal, and occipital lobes showed decreased nodal centrality. BvFTD patients showed the greatest decrease in inter-regional connectivity between the frontal and occipital regions, and the insular cortices and occipital, temporal, subcortical, and frontal regions. In bvFTD, altered global network properties correlated with executive dysfunction. Conclusions: Global and local functional networks are altered in bvFTD, suggesting a loss of efficiency in information exchange between both distant and close brain areas. Altered brain regions are located in structures that are closely associated with neuropathologic changes in bvFTD. Aberrant topology of the functional brain networks in bvFTD appears to underlie cognitive deficits in these patients.

Assessing the inter-rater agreement for ordinal data through weighted indexes

Assessing the inter-rater agreement between observers, in the case of ordinal variables, is an important issue in both the statistical theory and biomedical applications. Typically, this problem has been dealt with the use of Cohen’s weighted kappa, which is a modification of the original kappa statistic, proposed for nominal variables in the case of two observers. Fleiss (1971) put forth a generalization of kappa in the case of multiple observers, but both Cohen’s and Fleiss’ kappa could have a paradoxical behavior, which may lead to a difficult interpretation of their magnitude. In this paper, a modification of Fleiss’ kappa, not affected by paradoxes, is proposed, and subsequently generalized to the case of ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile and bootstrap-t confidence intervals based on this statistic. The normal asymptotic distribution of the proposed statistic is demonstrated. Our results are applied to the classical Holmquist et al.’s (1967) dataset on the classification, by multiple observers, of carcinoma in situ of the uterine cervix. Finally, we generalize the use of s* to a bivariate case.

pFDR and pFNR estimation for brain networks construction

Recent developments in the study of brain functional connectivity are widely based on graph theory. In the current analysis of brain networks, there is no unique way to derive the adjacency matrix, which is a useful representation for a graph. Its entries, containing information about the existence of links, are identified by thresholding the correlation between the time series that characterized the dynamic behavior of the nodes. In this work, we put forward a strategy to choose a suitable threshold on the correlation matrix considering the problem of multiple comparisons in order to control the error rates. In this context we propose to control the positive false discovery rate (pFDR) and a similar measure involving false negatives, called the positive false nondiscovery rate (pFNR). In particular, we provide point and interval estimators for pFNR and a method for balancing the two types of error, demonstrating it by using functional magnetic resonance imaging data and Monte Carlo simulations.

Contemporary Frequentist Views of the

The 2 × 2 table is the simplest of data structures yet it is of immense practical importance. It is also just complex enough to provide a theoretical testing ground for general frequentist methods. Yet after 70 years of debate, its correct analysis is still not settled. Rather than recount the entire history, our review is motivated by contemporary developments in likelihood and testing theory as well as computational advances. We will look at both conditional and unconditional tests. Within the conditional framework, we explain the relationship of Fisher’s test with variants such as mid-p and Liebermeister’s test, as well as modern developments in likelihood theory, such as p ∗ and approximate conditioning. Within an unconditional framework, we consider four modern methods of correcting approximate tests to properly control size by accounting for the unknown value of the nuisance parameter: maximisation (M), partial maximisation (B), estimation (E) and estimation followed by maximisation (E+M). Under the conditional model, we recommend Fisher’s test. For the unconditional model, amongst standard approximate methods, Liebermeister’s tests come closest to controlling size. However, our best recommendation is the E procedure applied to the signed root likelihood statistic, as this performs very well in terms of size and power and is easily computed. We support our assertions with a numerical study.

2\times2

Abstract This study aims to examine the possible presence of lead and cadmium in the liver and kidneys of hooded crows (Corvus cornix). Liver and kidneys of hooded crow carcasses were collected in Province of Cuneo (Piedmont, Italy) in order to detect lead and cadmium content. Significant differences were found in lead and cadmium levels between areas of intensive cultivation versus areas where meadows are prevalent. Moreover, age greatly influenced the burden of heavy metals, while sex did not seem to affect the level of contamination. The source of contamination may be phosphate fertilizers used for intensive cultivation in the study area.

Binomial Trial

Abstract In this paper we apply the s* statistic, aimed to measure the inter-rater agreement between observers in case of ordinal variables, to the evaluation of the quality of University courses. The objective is to measure the inter-rater agreement between students, along with their satisfaction, in order to verify the consistency of judgments expressed by independent observers. s* is a modification of a previously proposed index, which avoids the problem of paradoxes of Cohens and Fleiss’ kappa statistics. We present the s* index from both a descriptive and an inferential point of view. In particular, as far as statistical inference is concerned, we show that s* is a biased estimator of the inter-rater agreement in the population and, under the null hypothesis of inter-rater agreement by chance, s* is asymptotically normally distributed.

The Hooded Crow (Corvus cornix) as an Environmental Bioindicator Species of Heavy Metal Contamination

Line transect sampling is a distance sampling method widely used for estimating wildlife population density. Since the usual approach assumes a model for the detection function, the estimate depends on the shape of such a function. In particular, the estimate is influenced by the so-called shoulder condition, which ensures that detection is nearly certain at small distances from the line transect. For instance, the half-normal model satisfies this condition, whereas the negative exponential model does not. The aim of this paper is to propose the exponential mixture model of the half-normal and the negative exponential in order to estimate the population density in the case where the shoulder condition is not guaranteed. Such a case study on Hooded crow is described in the paper.

A Measure of Ordinal Concordance for the Evaluation of University Courses

In this paper we propose criteria for sexing Hooded Crow Corvus cornix, belonging to different age groups, in northwest Italy. Morphometric data were validated by molecular sexing, which offers a valid and reliable method to sex birds. The results suggest that tarsus and head + bill length provide the best biometric criteria for sex determination in the Hooded Crow, because these measurements do not change with age. We propose linear discriminant functions based on the tarsus and head + bill length, or on the head + bill length alone.

On estimating Hooded crow density from line transect data through exponential mixture models

In wildlife population studies one of the main goals is estimating the population abundance. Line transect sampling is a well established methodology for this purpose. The usual approach for estimating the density or the size of the population of interest is to assume a particular model for the detection function (the conditional probability of detecting an animal given that it is at a given distance from the observer). Two common models for this function are the half-normal model and the negative exponential model. The estimates are extremely sensitive to the shape of the detection function, particularly to the so-called shoulder condition, which ensures that an animal is almost certain to be detected if it is at a small distance from the observer. The half-normal model satisfies this condition whereas the negative exponential does not. Therefore, testing whether such a hypothesis is consistent with the data is a primary concern in every study aiming at estimating animal abundance. In this paper we propose a test for this purpose. This is the uniformly most powerful test in the class of the scale invariant tests. The asymptotic distribution of the test statistic is worked out by utilising both the half-normal and negative exponential model while the critical values and the power are tabulated via Monte Carlo simulations for small samples. .

Analysis of biometric and DNA data to determine the sex of Hooded Crows Corvus cornix in northwest Italy

ABSTRACT We propose a functional data analysis (FDA) approach based on capture–recapture data to fit growth curves to wild Mallard Anas platyrhynchos. For this purpose, growth curves are provided from weight measurements through smoothing based on a suitable expansion in terms of B-splines. In dealing with wild young birds the unknown date of hatching and the small number of recaptures represent challenging problems. Our results suggest that the size at fledging of wild Mallards is not the adult size; the adult weight is reached at 70–80 days. We have not noted weight losses in fledging young and so the metabolic cost of fledging does not seem to be high. Our statistical approach offers a valid way to quantify the growth of precocial birds.