scholarly journals Analysing Structures of Interregional Migration in England

2010 ◽  
pp. 280-293 ◽  
Author(s):  
James Raymer ◽  
Corrado Giulietti
Keyword(s):  
Linear Model ◽  
Interregional Migration ◽  
Migration Flow ◽  
Interaction Terms ◽  
Main Effect ◽  
Migration Flows ◽  
Log Linear ◽  
Ethnic Migration ◽  
Over Time ◽  
Model Fits

In this chapter, we explore the age and ethnic structures of interregional migration in England, as measured by the 1991 and 2001 Censuses. In doing so, we first analyse the main effect and two-way interaction components of migration flow tables cross-classified by (1) origin, destination and age and (2) origin, destination and ethnicity. Second, we test the significance of three-way interaction terms over time by comparing various unsaturated log-linear model fits. The aim is to identify the key structures in the migration flow tables and how they have changed over time. This is important for understanding the mechanisms underlying the more general patterns of migration. These analyses could also be used to inform the estimation or projection of migration flows. Our findings are that, despite a large increase in the levels of interregional migration, migration structures in England have remained fairly stable over time. The main changes have to do with the increases in the relative levels of ethnic migration over time, which has been unequal across space.

scholarly journals On the Estimation of Parameters and Best Model Fits of Log Linear Model for Contingency Table

OALib ◽  
2015 ◽  
Vol 02 (01) ◽  
pp. 1-11
Author(s):  
Cecilia N. Okoli ◽  
Sidney I. Onyeagu ◽  
George A. Osuji
Keyword(s):  
Linear Model ◽  
Contingency Table ◽  
Estimation Of Parameters ◽  
Log Linear ◽  
Model Fits

Asymptotic results for a conditional Poisson log-linear model

1989 ◽  
Vol 7 (4) ◽  
pp. 267-270 ◽  
Author(s):  
Douglas G Bonett ◽  
P.M Bentler ◽  
J.Arthur Woodward
Keyword(s):  
Linear Model ◽  
Asymptotic Results ◽  
Log Linear ◽  
Conditional Poisson

scholarly journals A Cascaded Unsupervised Model for PoS Tagging

2021 ◽  
Vol 20 (1) ◽  
pp. 1-23
Author(s):  
Necva Bölücü ◽  
Burcu Can
Keyword(s):  
Linear Model ◽  
Language Processing ◽  
Bayesian Model ◽  
Linear Models ◽  
Syntactic Category ◽  
Semantic Parsing ◽  
Pos Tagging ◽  
Part Of Speech ◽  
Sentence Level ◽  
Log Linear

Part of speech (PoS) tagging is one of the fundamental syntactic tasks in Natural Language Processing, as it assigns a syntactic category to each word within a given sentence or context (such as noun, verb, adjective, etc.). Those syntactic categories could be used to further analyze the sentence-level syntax (e.g., dependency parsing) and thereby extract the meaning of the sentence (e.g., semantic parsing). Various methods have been proposed for learning PoS tags in an unsupervised setting without using any annotated corpora. One of the widely used methods for the tagging problem is log-linear models. Initialization of the parameters in a log-linear model is very crucial for the inference. Different initialization techniques have been used so far. In this work, we present a log-linear model for PoS tagging that uses another fully unsupervised Bayesian model to initialize the parameters of the model in a cascaded framework. Therefore, we transfer some knowledge between two different unsupervised models to leverage the PoS tagging results, where a log-linear model benefits from a Bayesian model’s expertise. We present results for Turkish as a morphologically rich language and for English as a comparably morphologically poor language in a fully unsupervised framework. The results show that our framework outperforms other unsupervised models proposed for PoS tagging.

scholarly journals Differences in risk perception, knowledge and protective behaviour regarding COVID-19 by education level among women and men in Germany. Results from the COVID-19 Snapshot Monitoring (COSMO) study

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251694
Author(s):  
Petra Rattay ◽  
Niels Michalski ◽  
Olga Maria Domanska ◽  
Anna Kaltwasser ◽  
Freia De Bock ◽  
...  
Keyword(s):  
Risk Perception ◽  
Education Level ◽  
Factual Knowledge ◽  
Perceived Severity ◽  
Highly Educated ◽  
Interaction Terms ◽  
Protective Behaviour ◽  
Low Education ◽  
The Impact ◽  
Over Time

The main strategy for combatting SARS-CoV-2 infections in 2020 consisted of behavioural regulations including contact reduction, maintaining distance, hand hygiene, and mask wearing. COVID-19-related risk perception and knowledge may influence protective behaviour, and education could be an important determinant. The current study investigated differences by education level in risk perception, knowledge and protective behaviour regarding COVID-19 in Germany, exploring the development of the pandemic over time. The COVID-19 Snapshot Monitoring study is a repeated cross-sectional online survey conducted during the pandemic in Germany from 3 March 2020 (waves 1–28: 27,957 participants aged 18–74). Differences in risk perception, knowledge and protective behaviour according to education level (high versus low) were analysed using linear and logistic regression. Time trends were accounted for by interaction terms for education level and calendar week. Regarding protective behaviour, interaction terms were tested for all risk perception and knowledge variables with education level. The strongest associations with education level were evident for perceived and factual knowledge regarding COVID-19. Moreover, associations were found between low education level and higher perceived severity, and between low education level and lower perceived probability. Highly educated men were more worried about COVID-19 than those with low levels of education. No educational differences were observed for perceived susceptibility or fear. Higher compliance with hand washing was found in highly educated women, and higher compliance with maintaining distance was found in highly educated men. Regarding maintaining distance, the impact of perceived severity differed between education groups. In men, significant moderation effects of education level on the association between factual knowledge and all three protective behaviours were found. During the pandemic, risk perception and protective behaviour varied greatly over time. Overall, differences by education level were relatively small. For risk communication, reaching all population groups irrespective of education level is critical.

scholarly journals The Application of Log-Linear Model to Selected Poison Patients

2020 ◽  
pp. 1-7
Author(s):  
Fatin N.S.A. ◽  
Norlida M.N. ◽  
Siti Z.M.J.
Keyword(s):  
Linear Model ◽  
Linear Models ◽  
Demographic Data ◽  
Contingency Tables ◽  
Categorical Variables ◽  
State Variables ◽  
Exposure Route ◽  
Higher Dimensional ◽  
Route Of Exposure ◽  
Log Linear

Log-linear model is a technique used to analyze the cross-classification categorical data or the contingency table. It is used to obtain the parsimony models that describe the interaction between the categorical variables in contingency tables. Log-linear models are commonly used in evaluating higher dimensional contingency tables that involves more than two categorical variables. This study focuses on analyzing data of poisoned patients from 2012 to 2014 using log-linear model. There are two model analyzed; model for demographic data of patients and model of poisoning information. For the first model, the variables involved are gender, age, race and state. Variables for the second model are circumstance of exposure, type of exposure, location of exposure, route of exposure and types of poison. Both log-linear models are developed to investigate the association between variables in the model. As a result of this study, the best model for demographic data and poisoning information are the model with three-ways interaction. For the best model of demographic data, there is an association between gender, age and race, race, gender and state as well as age, race and state. Meanwhile, the best model for poisoning information reveals that there is relationship between circumstance of exposure, route of exposure and type of poison, location of exposure, route of exposure and type of poison, circumstance of exposure, type of exposure and route of exposure, circumstance of exposure, location of exposure and route of exposure, circumstance of exposure, type of exposure and type of poison and also type of exposure, location of exposure and type of poison. Keywords: log-linear; demographic; gender; age; race; state; circumstance of exposure; type of exposure; location of exposure; route of exposure; types of poison

scholarly journals Scrapie-resistant sheep show certain coat colour characteristics

2009 ◽  
Vol 91 (1) ◽  
pp. 39-46 ◽  
Author(s):  
R. M. SAWALHA ◽  
L. BELL ◽  
S. BROTHERSTONE ◽  
I. WHITE ◽  
A. J. WILSON ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Linear Model ◽  
Morphological Diversity ◽  
Coat Colour ◽  
Unintended Consequences ◽  
Colour Pattern ◽  
Reverse Pattern ◽  
Colour Patterns ◽  
Log Linear ◽  
The Relationship

SummarySusceptibility to scrapie is known to be associated with polymorphisms at the prion protein (PrP) gene, and this association is the basis of current selective programmes implemented to control scrapie in many countries. However, these programmes might have unintended consequences for other traits that might be associated withPrPgenotype. The objective of this study was to investigate the relationship betweenPrPgenotype and coat colour characteristics in two UK native sheep breeds valued for their distinctive coat colour patterns. Coat colour pattern, darkness and spotting andPrPgenotype records were available for 11 674 Badgerfaced Welsh Mountain and 2338 Shetland sheep. The data were analysed with a log–linear model using maximum likelihood. Results showed a strong significant association ofPrPgenotype with coat colour pattern in Badgerfaced Welsh Mountain and Shetland sheep and with the presence of white spotting in Shetland sheep. Animals with the ARR/ARR genotype (the most scrapie resistant) had higher odds of having a light dorsum and a dark abdomen than the reverse pattern. The implication of these associations is that selection to increase resistance to scrapie based only onPrPgenotype could result in change in morphological diversity and affect other associated traits such as fitness.

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