Heywood You Believe It? Heywood Cases Can Occur When Factor Analyzing Population-Level Dispersion Matrices with Model Error

2022 ◽  
pp. 1-1
Author(s):  
Allison W. Cooperman ◽  
Niels G. Waller
Keyword(s):  
Population Level ◽  
Model Error ◽  
Heywood Cases

Reduced model error analysis “application to synchronous machines"

1994 ◽  
Vol 4 (10) ◽  
pp. 1999-2012 ◽  
Author(s):  
Nabil Derbel ◽  
Mohamed B.A. Kamoun ◽  
Michel Poloujadoff
Keyword(s):  
Error Analysis ◽  
Model Error ◽  
Synchronous Machines ◽  
Reduced Model ◽  
Analysis Application

P032 E-CIGARETTE AND CIGARETTE USE AMONG U.S. ADULT IBD PATIENTS: POPULATION-LEVEL SURVEY

2020 ◽  
Vol 158 (3) ◽  
pp. S102
Author(s):  
Ryan Suk ◽  
Heetae Suk ◽  
Kalyani Sonawane ◽  
Ashish Deshmukh
Keyword(s):  
Population Level ◽  
Cigarette Use

Cranial crassicaudiasis in two coastal dolphin species from South Africa is predominantly a disease of immature individuals

2020 ◽  
Vol 139 ◽  
pp. 93-102 ◽  
Author(s):  
MF Van Bressem ◽  
P Duignan ◽  
JA Raga ◽  
K Van Waerebeek ◽  
N Fraijia-Fernández ◽  
...  
Keyword(s):  
South Africa ◽  
Bone Development ◽  
Bottlenose Dolphins ◽  
Fatal Outcome ◽  
Population Level ◽  
Cape Coast ◽  
Osteolytic Lesions ◽  
Immune Mediated ◽  
Significant Difference ◽  
The Difference

Crassicauda spp. (Nematoda) infest the cranial sinuses of several odontocetes, causing diagnostic trabecular osteolytic lesions. We examined skulls of 77 Indian Ocean humpback dolphins Sousa plumbea and 69 Indo-Pacific bottlenose dolphins Tursiops aduncus, caught in bather-protecting nets off KwaZulu-Natal (KZN) from 1970-2017, and skulls of 6 S. plumbea stranded along the southern Cape coast in South Africa from 1963-2002. Prevalence of cranial crassicaudiasis was evaluated according to sex and cranial maturity. Overall, prevalence in S. plumbea and T. aduncus taken off KZN was 13 and 31.9%, respectively. Parasitosis variably affected 1 or more cranial bones (frontal, pterygoid, maxillary and sphenoid). No significant difference was found by gender for either species, allowing sexes to be pooled. However, there was a significant difference in lesion prevalence by age, with immature T. aduncus 4.6 times more likely affected than adults, while for S. plumbea, the difference was 6.5-fold. As severe osteolytic lesions are unlikely to heal without trace, we propose that infection is more likely to have a fatal outcome for immature dolphins, possibly because of incomplete bone development, lower immune competence in clearing parasites or an over-exuberant inflammatory response in concert with parasitic enzymatic erosion. Cranial osteolysis was not observed in mature males (18 S. plumbea, 21 T. aduncus), suggesting potential cohort-linked immune-mediated resistance to infestation. Crassicauda spp. may play a role in the natural mortality of S. plumbea and T. aduncus, but the pathogenesis and population level impact remain unknown.

Population level risk factors associated with childhood obesity

2019 ◽  
Author(s):  
Claire Beynon ◽  
Nora Pashyan ◽  
Elizabeth Fisher ◽  
Dougal Hargreaves ◽  
Linda Bailey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Childhood Obesity ◽  
Population Level ◽  
Factors Associated

Hungarian diet and nutritional status survey – The OTAP2009 study I. Nutritional status of the Hungarian population

2012 ◽  
Vol 153 (26) ◽  
pp. 1023-1030 ◽  
Author(s):  
Éva Martos ◽  
Viktória Anna Kovács ◽  
Márta Bakacs ◽  
Csilla Kaposvári ◽  
Andrea Lugasi
Keyword(s):  
Nutritional Status ◽  
Abdominal Obesity ◽  
Public Health Problem ◽  
Participation Rate ◽  
Population Level ◽  
Prevalence Of Obesity ◽  
Interview Survey ◽  
European Health ◽  
European Health Interview Survey ◽  
And Gender

Obesity is a leading public health problem, but representative data on measured prevalence among Hungarian adults has been missing since the late eighties. Aim and method: Joining in European Health Interview Survey the aim of the OTAP2009 study was to provide data representative by age and gender on the prevalence of obesity and abdominal obesity among Hungarian adults based on their measured anthropometric data. Results: Participation rate was 35% (n = 1165). Data shows that nearly two-thirds of adults are overweight or obese. 26.2% of men and 30.4% of women are obese. Prevalence of morbid obesity is 3.1% and 2.6% in men and women, respectively. Abdominal obesity is more prevalent among women than men (51.0% vs. 33.2%), and rate is increasing parallel with age in both gender. In elderly, 55% of men and almost 80% of women are abdominally obese. Conclusions: Besides interventions of population level for tackling obesity, individual preventive measures are indispensable. Orv. Hetil., 2012, 153, 1023–1030.

‘Mass’ deaths of mooseAlces alcesin southern Sweden: population level characterisation

2002 ◽  
Vol 8 (1) ◽  
pp. 219-228 ◽  
Author(s):  
Emil Broman ◽  
Kjell Wallin ◽  
Margareta Steén ◽  
Göran Cederlund
Keyword(s):  
Population Level ◽  
Southern Sweden

PENERAPAN CLUSTERING PADA PENDUDUK YANG MEMPUNYAI KELUHAN KESEHATAN DENGAN DATAMINING K-MEANS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Nurul Rofiqo ◽  
Agus Perdana Windarto ◽  
Dedy Hartama
Keyword(s):  
Public Health ◽  
Data Mining ◽  
Population Level ◽  
Research Data ◽  
Health Complaints ◽  
Public Health Services ◽  
National Statistics ◽  
Central Java ◽  
Indonesian Population ◽  
The Government

This study aims to utilize Clushtering Algorithm in grouping the number of people who have health complaints with the K-means algorithm in Indonesia. The source of this research data was collected based on the documents of the provincial population which had health complaints produced by the National Statistics Agency. The data used in this study are data from 2013-2017 consisting of 34 provinces. The method used in this research is K-means Algorithm. Data will be processed by clushtering in 3 clushter, namely clusther high health complaints, clusther moderate and low health complaints. Centroid data for high population level clusters 37.48, Centroid data for moderate population level clusters 27.08, and Centroid data for low population level clusters 14.89. So that obtained an assessment based on the population index that has health complaints with 7 provinces of high health complaints, namely Central Java, Yogyakarta, Bali, West Nusa Tenggara, East Nusa Tenggara, South Kalimantan, Gorontalo, 18 provinces of moderate health complaints, and 9 other provinces including low health complaints. This can be an input to the government to give more attention to residents in each region who have high health complaints through improving public health services so that the Indonesian population becomes healthier without health complaints.Keywords: data mining, health complaints, clustering, K-means, Indonesian residents

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