Context-Specific independencies embedded in Chain Graph Models of type I

For a set of variables collected in a contingency table, we focus on a particular kind of relationships such as the context-specific independencies. These are conditional independencies that hold for particular values of the conditioning set. Given the advantages of the graphical models, we use them to represent different relationships among the variables, including the context-specific independencies. In particular, we enrich chain graph models with labelled arcs. Furthermore, we consider the well-known relationships between chain graph models and hierarchical multinomial marginal models and we introduce new constraints on parameters in order to describe the context-specific relationship. Finally, we provide an application to the study of innovation in Italy by comparing two different periods

Context-specific independencies in hierarchical multinomial marginal models

This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the hierarchical multinomial marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises

Context-specific independencies in Hierarchical Multinomial Marginal models

This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the Hierarchical Multinomial Marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises

Improving the power of hypothesis tests in sparse contingency tables

When analyzing data in contingency tables it is frequent to deal with sparse data, particularly when the sample size is small relative to the number of cells. Most analyses of this kind are interpreted in an exploratory manner and even if tests are performed, little attention is paid to statistical power. This paper proposes a method we call redundant procedure, which is based on the union–intersection principle and increases test power by focusing on specific components of the hypothesis. This method is particularly helpful when the hypothesis to be tested can be expressed as the intersections of simpler models, such that at least some of them pertain to smaller table marginals. This situation leads to working on tables that are naturally denser. One advantage of this method is its direct application to (chain) graphical models. We illustrate the proposal through simulations and suggest strategies to increase the power of tests in sparse tables. Finally, we demonstrate an application to the EU-SILC dataset

Investigating masking effects of age trends on the correlations among tree ring proxies

Age-related trends are present in tree-ring widths (TRW), but their presence in tree rings isotope is debated. It is unclear how cambial age influences the relationships between TRW and isotopes. Tree-ring isotopes of alpine larch and cembran-pine trees showed only trends in the juvenile period (>100 years), which might mask the inter-relations between tree-ring proxies during cambial age. This work tries to unmask the age-trend influences by examining the correlations in TRW-stable isotopes with and without age-trend correction. The non-detrended and linear-detrended values of TRW, of δD and δ18O showed significant correlations for ages up to 100 years, but not afterward. However, the correlation values, after spline or first-difference time-series detrending, were not age-related. Thus, detrending methods affect the correlations in the juvenile phase and may affect climate-related interpretations. The correlations between TRW and δ13C were not age-related, while those among the isotopes were significant throughout the ages. The correlation between δ13C and δD was the exception, as it became significant only after age > 100 years, suggesting a different use of reserves in the juvenile phase. In conclusion, the relationships among the tree-ring parameters are stable in all the different detrend scenarios after the juvenile phase, and they can be used together in multi-proxy paleoclimatic studies. The data of the juvenile phase can be used after spline-detrending or first-difference time-series calculation, depending on the purpose of the analysis to remove age-related trends. The work also provides clues on the possible causes of juvenile age trends

Context-specific independence in innovation study

The study of (in)dependence relationships among a set of categorical variables collected in a contingency table is an amply topic. In this work we want to focus on the so called context-specific independence where the conditional independence holds only in a subspace of the outcome space. The main aspects that we introduce concern the definition in the same model of marginal, conditional and context-specific independencies, through the marginal models. Furthermore, we investigate how it is possible to test these context-specific independencies when there are ordinal variables. Finally, we propose a graphical representation of all the considered independencies taking advantages from the chain graph model. We show the results on an application on \u201dThe Italian Innovation Survey\u201d of Istat (2012)

A novel BRCA2 splice variant identified in a young woman

Background: BRCA1/2 VUSs represent an important clinical issue in risk assessment for the breast/ovarian cancer families (HBOC) families. Among them, some occurring within the intron-exon boundary may lead to aberrant splicing process by altering or creating de novo splicing regulatory elements or unmasking cryptic splice site. Defining the impact of these potential splice variants at functional level is important to establish their pathogenic role. Methods: Genomic DNA was extracted from peripheral blood sample of a young woman affected with breast cancer belonging to a HBOC family and the entire coding regions of the BRCA1 and BRCA2 genes were amplified using the Ion AmpliSeq BRCA1 and BRCA2 Panel. The BRCA2 c.682-2delA variant has been characterized by RT-PCR analysis performed on mRNA extracted from blood and lymphoblastoid cell line. Results: We demonstrated that a novel BRCA2 c.682-2delA variant at the highly conserved splice consensus site in intron 8 disrupts the canonical splice acceptor site generating a truncated protein as predicted by several bioinformatics tools. Segregations analysis in the family and LOH performed on proband breast cancer tissue further confirmed its classification as pathogenic variant. Conclusion: Combining different methodologies, we characterized this new BRCA2 variant and provided findings of clinical utility for its classification as pathogenic variant