scholarly journals Cluster analysis of domestic mites and associated housing conditions in concrete-built apartments in Nagoya, Japan

1996 ◽  
Vol 47 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Ikuko SAKAKI ◽  
Chiharu SUTO
Keyword(s):  
Cluster Analysis ◽  
Housing Conditions ◽  
Domestic Mites

scholarly journals Desenvolvimento Socioeconômico nas microrregiões do Paraná: uma análise multivariada

2012 ◽  
Vol 38 (2) ◽  
Author(s):  
Vinícius Gonçalves Vidigal ◽  
Isis De Castro Amaral ◽  
Glauber Flaviano Silveira
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Regional Differences ◽  
Industrial Development ◽  
Socioeconomic Development ◽  
Housing Conditions ◽  
Multivariate Statistical ◽  
Group 2 ◽  
Development Levels ◽  
The One

Este trabalho teve como objetivo avaliar as diferenças de nível de desenvolvimento socioeconômico entre as microrregiões do Estado do Paraná, bem como hierarquizá-las e, posteriormente, agrupá-las de acordo com suas principais características. Utilizou-se para tanto a análise estatística multivariada. Os principais resultados demonstraram a existência de disparidades regionais, a partir de indicadores de condições de moradia, de precariedade dos serviços de saúde e de desenvolvimento industrial, obtidos a partir da análise fatorial. A análise de cluster distribuiu as microrregiões em cinco grupos, sendo que o Grupo 2, formado pelos municípios de Cerro Azul e Pitanga, foi aquele com as piores condições de desenvolvimento. Todos os demais grupos apresentaram resultado negativo em apenas um dos três indicadores. Portanto, observa-se que coexistem carências extremamente importantes e que afetam milhares de famílias em todo o Estado do Paraná.Abstract: This study had as objective to evaluate the differences in socioeconomic development levels among regions of Paraná State, as well as rank and then groupthem according to their main characteristics. The methodological tools refer to techniques of multivariate statistical analysis which were factor and clusteranalysis. The main results showed the existence of great regional differences, considering indicators of housing conditions, precarious health services and industrial development, all obtained from the factor analysis. The cluster analysis distributed the regions in five groups, in which Group 2 was the one with the worst conditions of development. All other groups showed a negative result in only one of the three indicators. Therefore, it is observed that exist extremely important needs that affect thousands of families throughout the state of Paraná.

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

Measuring “Language Access Profiles” in Deaf and Hard-of-Hearing Children With the DHH Language Exposure Assessment Tool

2020 ◽  
pp. 1-25
Author(s):  
Matthew L. Hall ◽  
Stephanie De Anda
Keyword(s):  
Cluster Analysis ◽  
Exposure Assessment ◽  
Hard Of Hearing ◽  
Assessment Tool ◽  
Communication Mode ◽  
Developmental Potential ◽  
Language Access ◽  
Retest Reliability ◽  
Language Exposure ◽  
Test Retest Reliability

Purpose The purposes of this study were (a) to introduce “language access profiles” as a viable alternative construct to “communication mode” for describing experience with language input during early childhood for deaf and hard-of-hearing (DHH) children; (b) to describe the development of a new tool for measuring DHH children's language access profiles during infancy and toddlerhood; and (c) to evaluate the novelty, reliability, and validity of this tool. Method We adapted an existing retrospective parent report measure of early language experience (the Language Exposure Assessment Tool) to make it suitable for use with DHH populations. We administered the adapted instrument (DHH Language Exposure Assessment Tool [D-LEAT]) to the caregivers of 105 DHH children aged 12 years and younger. To measure convergent validity, we also administered another novel instrument: the Language Access Profile Tool. To measure test–retest reliability, half of the participants were interviewed again after 1 month. We identified groups of children with similar language access profiles by using hierarchical cluster analysis. Results The D-LEAT revealed DHH children's diverse experiences with access to language during infancy and toddlerhood. Cluster analysis groupings were markedly different from those derived from more traditional grouping rules (e.g., communication modes). Test–retest reliability was good, especially for the same-interviewer condition. Content, convergent, and face validity were strong. Conclusions To optimize DHH children's developmental potential, stakeholders who work at the individual and population levels would benefit from replacing communication mode with language access profiles. The D-LEAT is the first tool that aims to measure this novel construct. Despite limitations that future work aims to address, the present results demonstrate that the D-LEAT represents progress over the status quo.

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