A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns

An extensive investigation via simulation is carried out with the aim of comparing three nonparametric, single imputation methods in the presence of multiple data patterns. The ultimate goal is to provide useful hints for users needing to quickly pick the most effective impu- tation method among the following: Forward Imputation (ForImp), considered in the two variants of ForImp with the principal compo- nent analysis (PCA), which alternates the use of PCA and the Nearest- Neighbour Imputation (NNI) method in a forward, sequential pro- cedure, and ForImp with the Mahalanobis distance, which involves the use of the Mahalanobis distance when performing NNI; the itera- tive PCA technique, which imputes missing values simultaneously via PCA; the missForest method, which is based on random forests and is developed for mixed-type data. The performance of these methods is compared under several data patterns characterized by different levels of kurtosis or skewness and correlation structures

Experiência em pesquisa: a trajetória do Grupo de Pesquisa em usuários de informação

Se comparte la trayectoria del Grupo de Investigación sobre Usuarios de la Información perteneciente a la cátedra “Usuarios de la Información” de la Escuela de Bibliotecología, Facultad de Filosofía y Humanidades de la Universidad Nacional de Córdoba, Argentina. Se muestra la evolución, desarrollo y crecimiento del mismo, así como de las investigadoras que lo integran. Se exponen y explican brevemente las investigaciones realizadas y la investigación en curso, partiendo de la teoría de la sociedad de las tecnologías de la información (Castells, 2002), de las que aportaron a la evolución de la alfabetización en información (Kunhlthau - 1987; Bruce - 1997, Eisenberg - 1998, SCONUL - 1999; ACRL - 1989; Webber y Johnson - 2002; Walter - 2007 y UNESCO - 2008). Como así también las teorías de Aprendizaje de Bruner, Ausubel y Vygotsky. Se finaliza la presente ponencia realizando una proyección sobre el futuro de este grupo tomando como referencia los frutos resultantes de las investigaciones que marcaron esta trayectoria

Algorithmic-type imputation techniques with different data structures : alternative approaches in comparison

In recent years, with the spread availability of large datasets from multiple sources, increasing attention has been devoted to the treatment of missing information. Recent approaches have paved the way to the development of new powerful algorithmic techniques, in which imputation is performed through computer-intensive procedures. Although most of these approaches are attractive for many reasons, less attention has been paid to the problem of which method should be preferred according to the data structure at hand. This work addresses the problem by comparing the two methods missForest and IPCA with a new method we developed within the forward imputation approach. We carried out comparisons by considering different data patterns with varying skewness and correlation of variables, in order to ascertain in which situations a given method produces more satisfying result

Algorithmic imputation techniques for missing data : performance comparisons and development perspectives

In recent years, much research has been devoted to solve the problem of missing data imputation. Although most of the novel proposals look attractive for some reason, less attention has been paid to the problem of when and why a particular method should be chosen while discarding the others. This matter is far crucial in applications, given that unsuitable solutions could heavily affect the reliability of statistical analyses. Starting from this, this work is addressed to study how well several algorithmic-type imputation methods perform in the case of quantitative data. We focus on three different logics of imputing, based respectively on the use of random forests, iterative PCA, and the forward procedure. In particular, the latter, having initially been introduced for ordinal data, has required us to develop an original adaptation so that it handles missing quantitative value

A Comprehensive Simulation Study on the Forward Imputation

The Nearest Neighbour Imputation (NNI) method has a long history in missing data imputation. Likewise, multivariate dimensional reduction techniques allow for preserving the maximum information from the data. Recently, the combined use of these methodologies has been proposed to solve data imputation problems and exploit as much as information from the complete part of the data. In this paper we perform an extensive simulation study to test the performance of this new imputation approach (called \u201cForward Imputation\u201d - ForImp). We compare the two ForImp methods developed for missing quantitative data (the first one called ForImpPCA involving the NNI method and the Principal Component Analysis (PCA) as a multivariate data analysis technique, and the second one called ForImpMahalanobis, which involves the Mahalanobis distance for NNI) with other two imputation techniques regarded as benchmark, namely Stekhoven and B\ufchlmann\u2019s missForest method, which is a nonparametric imputation technique for continuous and/or categorical data based on a random forest, and the Iterative PCA, which is an algorithmic-type technique that imputes missing values simultaneously by an iterative use of PCA. The simulation study is based on constructing simulated data with different levels of kurtosis or skewness and strength of linear relationship of variables, so that the performance of the four methods can be compared on various data patterns. Distributions used for these simulated data belong to the families of Multivariate Exponential Power and Multivariate Skew-Normal distributions, respectively. Results tend to favour ForImpMahalanobis especially in the presence of skew data with small or negative correlations of a same magnitude, or a mix of negative and positive correlations of low level, whereas ForImpPCA works better than it when a slightly higher level of correlations is present in the data

Experiência em pesquisa: a trajetória do Grupo de Pesquisa em usuários de informação

Se comparte la trayectoria del Grupo de Investigación sobre Usuarios de la Información perteneciente a la cátedra “Usuarios de la Información” de la Escuela de Bibliotecología, Facultad de Filosofía y Humanidades de la Universidad Nacional de Córdoba, Argentina. Se muestra la evolución, desarrollo y crecimiento del mismo, así como de las investigadoras que lo integran. Se exponen y explican brevemente las investigaciones realizadas y la investigación en curso, partiendo de la teoría de la sociedad de las tecnologías de la información (Castells, 2002), de las que aportaron a la evolución de la alfabetización en información (Kunhlthau - 1987; Bruce - 1997, Eisenberg - 1998, SCONUL - 1999; ACRL - 1989; Webber y Johnson - 2002; Walter - 2007 y UNESCO - 2008). Como así también las teorías de Aprendizaje de Bruner, Ausubel y Vygotsky. Se finaliza la presente ponencia realizando una proyección sobre el futuro de este grupo tomando como referencia los frutos resultantes de las investigaciones que marcaron esta trayectoria

Volcanic spreading of Vesuvius, a new paradigm for interpreting its volcanic activity

We integrate geologic, structural, leveling and Differential SAR Interferometry data to show that Vesuvius began to spread onto its sedimentary substratum about 3,600 years ago. Moreover, we model the detected deformation with a solution of the lubrication approximation of the Navier-Stokes equations to show that spreading may continue for about 7,200 years more. Correlation of volcanic spreading with phases of the eruptive activity suggests that Plinian eruptions, which are thought to pose the major hazard, are less likely to occur in the near future.Published1-4partially_ope

Developing cardiac and skeletal muscle share fast-skeletal myosin heavy chain and cardiac troponin-I expression

Skeletal muscle derived stem cells (MDSCs) transplanted into injured myocardium can differentiate into fast skeletal muscle specific myosin heavy chain (sk-fMHC) and cardiac specific troponin-I (cTn-I) positive cells sustaining recipient myocardial function. We have recently found that MDSCs differentiate into a cardiomyocyte phenotype within a three-dimensional gel bioreactor. It is generally accepted that terminally differentiated myocardium or skeletal muscle only express cTn-I or sk-fMHC, respectively. Studies have shown the presence of non-cardiac muscle proteins in the developing myocardium or cardiac proteins in pathological skeletal muscle. In the current study, we tested the hypothesis that normal developing myocardium and skeletal muscle transiently share both sk-fMHC and cTn-I proteins. Immunohistochemistry, western blot, and RT-PCR analyses were carried out in embryonic day 13 (ED13) and 20 (ED20), neonatal day 0 (ND0) and 4 (ND4), postnatal day 10 (PND10), and 8 week-old adult female Lewis rat ventricular myocardium and gastrocnemius muscle. Confocal laser microscopy revealed that sk-fMHC was expressed as a typical striated muscle pattern within ED13 ventricular myocardium, and the striated sk-fMHC expression was lost by ND4 and became negative in adult myocardium. cTn-I was not expressed as a typical striated muscle pattern throughout the myocardium until PND10. Western blot and RT-PCR analyses revealed that gene and protein expression patterns of cardiac and skeletal muscle transcription factors and sk-fMHC within ventricular myocardium and skeletal muscle were similar at ED20, and the expression patterns became cardiac or skeletal muscle specific during postnatal development. These findings provide new insight into cardiac muscle development and highlight previously unknown common developmental features of cardiac and skeletal muscle. © 2012 Clause et al

May a unitary autonomic index help assess autonomic cardiac regulation in elite athletes? Preliminary observations on the national Italian Olympic committee team

Long term endurance training, as occurring in elite athletes, is associated to cardiac neural remodeling in favor of cardioprotective vagal mechanisms, resulting in resting bradycardia and augmented contribution of cardiac parasympathetic nerve activity. Autonomic assessment can be performed by way of Heart Rate Variability. This technique however provides multiple indices, and there is not yet complete agreement on their specific significance. Purpose of the study was to assess whether a rank transformation and radar plot could provide a unitary autonomic index, capable to show a correlation between intensity of individual work and quality of autonomic regulation