Visualization of the Significant Explicative Categories using Catanova Method and Non-Symmetrical Correspondence Analysis for Evaluation of Passenger Satisfaction

ANalysis Of VAriance (ANOVA) is a method to decompose the total variation of the observations into sum of variations due to different factors and the residual component. When the data are nominal, the usual approach of considering the total variation in response variable as measure of dispersion about the mean is not well defined. Light and Margolin (1971) proposed CATegorical ANalysis Of VAriance (CATANOVA), to analyze the categorical data. Onukogu (1985) extended the CATANOVA method to two-way classified nominal data. The components (sums of squares) are, however, not orthogonal. Singh (1996) developed a CATANOVA procedure that gives orthogonal sums of squares and defined test statistics and their asymptotic null distributions. In order to study which exploratory categories are influential factors for the response variable we propose to apply Non-Symmetrical Correspondence Analysis (D'Ambra and Lauro, 1989) on significant components. Finally, we illustrate the analysis numerically, with a practical example

Generalized log odds ratio analysis for the association in two-way contingency table.

The odds ratio is a measure of association used both for the analysis of a contingency table and an contingency table, where I and J are bigger than 2. Nevertheless, the total number of odds ratios to check grows with I and J and several methods have been developed to summarize them. In the present paper we present a general framework for the analysis of the complete set of log odds ratio. Particularly we propose and connect two different methodologies performed on two different data sets. Moreover starting from these methodologies, we focus our attention on the factorial representation of the log odds ratios

Is the United States Claims Court Constitutional?

This article will deal with two major constitutional problems that have resulted from the creation of the Claims Court. The first issue is the constitutionality of the appointment of existing Court of Claims Commissioners to be judges on the Claims Court during a four-year transition period. By legislatively designating the persons who are to serve as judges on the new court, Congress has usurped the presidential appointment power. The second issue relates to the constitutional status of the Claims Court. The Court of Claims which it replaces was created under article III of the Constitution, and the judges on it were therefore entitled to life tenure and salaries that could not be reduced during their terms in office. The new Claims Court, on the other hand, is designated by Congress as an article I court; the judges are to be appointed for only fifteen year terms, and their salaries are subject to control by Congress. The new court exercises full judicial authority, however, and has jurisdiction over cases of national importance in which the government of the United States has a great financial stake. Although the analysis of this issue is far from simple, this author concludes that Congress has exceeded its constitutional authority by failing to comply with the requirements of article III of the Constitution in establishing the Claims Court

Tackling the jelly web: Trophic ecology of gelatinous zooplankton in oceanic food webs of the eastern tropical Atlantic assessed by stable isotope analysis

Gelatinous zooplankton can be present in high biomass and taxonomic diversity in planktonic oceanic food webs, yet the trophic structuring and importance of this “jelly web” remain incompletely understood. To address this knowledge gap, we provide a holistic trophic characterization of a jelly web in the eastern tropical Atlantic, based on δ13C and δ15N stable isotope analysis of a unique gelatinous zooplankton sample set. The jelly web covered most of the isotopic niche space of the entire planktonic oceanic food web, spanning > 3 trophic levels, ranging from herbivores (e.g., pyrosomes) to higher predators (e.g., ctenophores), highlighting the diverse functional roles and broad possible food web relevance of gelatinous zooplankton. Among gelatinous zooplankton taxa, comparisons of isotopic niches pointed to the presence of differentiation and resource partitioning, but also highlighted the potential for competition, e.g., between hydromedusae and siphonophores. Significant differences in spatial (seamount vs. open ocean) and depth‐resolved patterns (0–400 m vs. 400–1000 m) pointed to additional complexity, and raise questions about the extent of connectivity between locations and differential patterns in vertical coupling between gelatinous zooplankton groups. Added complexity also resulted from inconsistent patterns in trophic ontogenetic shifts among groups. We conclude that the broad trophic niche covered by the jelly web, patterns in niche differentiation within this web, and substantial complexity at the spatial, depth, and taxon level call for a more careful consideration of gelatinous zooplankton in oceanic food web models. In light of climate change and fishing pressure, the data presented here also provide a valuable baseline against which to measure future trophic observations of gelatinous zooplankton communities in the eastern tropical Atlantic

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Visualization of the Significant Explicative Categories using Catanova Method and Non-Symmetrical Correspondence Analysis for Evaluation of Passenger Satisfaction

ANalysis Of VAriance (ANOVA) is a method to decompose the total variation of the observations into sum of variations due to different factors and the residual component. When the data are nominal, the usual approach of considering the total variation in response variable as measure of dispersion about the mean is not well defined. Light and Margolin (1971) proposed CATegorical ANalysis Of VAriance (CATANOVA), to analyze the categorical data. Onukogu (1985) extended the CATANOVA method to two-way classified nominal data. The components (sums of squares) are, however, not orthogonal. Singh (1996) developed a CATANOVA procedure that gives orthogonal sums of squares and defined test statistics and their asymptotic null distributions. In order to study which exploratory categories are influential factors for the response variable we propose to apply Non-Symmetrical Correspondence Analysis (D'Ambra and Lauro, 1989) on significant components. Finally, we illustrate the analysis numerically, with a practical example

The association in a two-way contingency table through log odds ratio analysis: the case of Sarno river pollution

In this paper we are proposing a general framework for the analysis of the complete set of log Odds Ratios (ORs) generated by a two-way contingency table. Starting from the RC (M) association model and hypothesizing a Poisson distribution for the counts of the two-way contingency table we are obtaining the weighted Log Ratio Analysis that we are extending to the study of log ORs. Particularly we are obtaining an indirect representation of the log ORs and some synthesis measures. Then for studying the matrix of log ORs we are performing a generalized Singular Value Decomposition that allows us to obtain a direct representation of log ORs. We also expect to get summary measures of association too. We have considered the matrix of complete set of ORs, because, it is linked to the two-way contingency table in terms of variance and it allows us to represent all the ORs on a factorial plan. Finally, a two-way contingency table, which crosses pollution of the Sarno river and sampling points, is to be analyzed to illustrate the proposed framework