Log-linear modelling of spatial interaction

1983 ◽  
Vol 52 (1) ◽  
pp. 187-205 ◽  
Author(s):  
Frans Willekens
Keyword(s):  
Spatial Interaction ◽  
Linear Modelling ◽  
Log Linear

Stemmen in Vlaanderen op 13 december 1987 : Een statistische analyse

Res Publica ◽  
1988 ◽  
Vol 30 (1) ◽  
pp. 25-50
Author(s):  
Marc Swyngedouw ◽  
Jaak Billiet
Keyword(s):  
Political Parties ◽  
Democratic Party ◽  
Occupational Status ◽  
The Political ◽  
Voting Behaviour ◽  
National Elections ◽  
Statistische Analyse ◽  
Use Of Data ◽  
Linear Modelling ◽  
Log Linear

Taking into account the limits of such data, this study analyses the shifts in voting behaviour from the national elections in 1985 to those in 1987 in Flanders, using log-linear modelling. The use of data from poll surveys for estimating shifts between subsequent elections poses some methodological problems.The second part presents the results of the analysis. About 13,51 % of -the 1985-voters switched. Although there are significant shifts between all the political parties, the Christian Democratic Party (CVP) loses on all fronts. A log-linear analysis of party-reference by sex, age and occupational status shows the strength and weakness of each party in different societal categories. In conclusion, an interpretation of the shifts is proposed. The following factors can account for the major shifts : the desintegration of the catholic pillar, the emergence of a dual society, the affinity between neo-liberalism and yuppie-culture and the conflict between the language communities.

Characterizing adaptations of serve indicators in top-level male volleyball among seasons

2020 ◽  
pp. 174795412097892
Author(s):  
Konstantinos Sotiropoulos ◽  
Sotirios Drikos ◽  
Sophia D Papadopoulou ◽  
Karolina Barzouka
Keyword(s):  
Correspondence Analysis ◽  
Olympic Games ◽  
Multiple Correspondence Analysis ◽  
Horizontal Axis ◽  
Special Focus ◽  
Linear Modelling ◽  
Chi Squared ◽  
Position Type ◽  
Log Linear

The purpose of this study was to analyse selected serve characteristics in top-level male volleyball, with a special focus on detecting adaptations of the serve skill among seasons. The indicators examined were type, position, direction and quality of serve. The sample consisted of 5482 serves from three final phases of different top-level tournaments (Olympic Games 2012, N = 1942, World League 2017, N = 1883, World Championship 2018, N = 1657). The interrelationships between variables were analyzed using chi-squared tests, log-linear modelling and multiple correspondence analysis. The results showed that the interaction of all serve indicators are statistically important, but the combination of the variables’ categories that were more responsible for association alternated across the seasons under study. A 3-way association term was revealed for season 2012 (type/position/direction) and 2018 (type/position/quality), while for season 2017 multiple 2-way interactions were found (type/position, type/direction, position/quality, direction/quality). The direction of the serve to the horizontal axis of the court was correlated to the quality of serve and consequently with the advantage of the serving team, while a more tactical perspective for serve skill is formed over periods in top level male volleyball.

Functional Form and Spatial Interaction Models

1998 ◽  
Vol 30 (8) ◽  
pp. 1497-1507 ◽  
Author(s):  
T J Fik ◽  
G F Mulligan
Keyword(s):  
Labor Migration ◽  
Functional Form ◽  
Spatial Interaction ◽  
Dummy Variables ◽  
Interaction Models ◽  
Spatial Interaction Models ◽  
Transformation Procedure ◽  
Interaction Modeling ◽  
Functional Forms ◽  
Log Linear

This paper is an examination of functional form and functional misspecification in regression-based spatial interaction models. Box–Cox transformations are used to model US state-to-state labor migration. Attention is given to the production-constrained gravity model, the competing and intervening destinations (CID) model, and an extension of the CID model which uses dummy variables and an iterative transformation procedure. Statistical evidence supports the argument that the use of highly restrictive log-linear specifications may be inappropriate and problematic. Implications for spatial interaction modeling using general nonrestrictive functional forms are discussed.

scholarly journals Estimating the number of injecting drug users in Scotland's HCV-diagnosed population using capture–recapture methods

2013 ◽  
Vol 142 (1) ◽  
pp. 200-207 ◽  
Author(s):  
S. A. McDONALD ◽  
S. J. HUTCHINSON ◽  
C. SCHNIER ◽  
A. McLEOD ◽  
D. J. GOLDBERG
Keyword(s):  
Linked Data ◽  
Drug Users ◽  
Surveillance Systems ◽  
Treatment Interventions ◽  
Public Health Professionals ◽  
Combining Data ◽  
Linear Modelling ◽  
Capture Recapture ◽  
Hcv Antibody ◽  
Log Linear

SUMMARYIn countries maintaining national hepatitis C virus (HCV) surveillance systems, a substantial proportion of individuals report no risk factors for infection. Our goal was to estimate the proportion of diagnosed HCV antibody-positive persons in Scotland (1991–2010) who probably acquired infection through injecting drug use (IDU), by combining data on IDU risk from four linked data sources using log-linear capture–recapture methods. Of 25 521 HCV-diagnosed individuals, 14 836 (58%) reported IDU risk with their HCV diagnosis. Log-linear modelling estimated a further 2484 HCV-diagnosed individuals with IDU risk, giving an estimated prevalence of 83. Stratified analyses indicated variation across birth cohort, with estimated prevalence as low as 49% in persons born before 1960 and greater than 90% for those born since 1960. These findings provide public-health professionals with a more complete profile of Scotland's HCV-infected population in terms of transmission route, which is essential for targeting educational, prevention and treatment interventions.

What is the ‘real’ admission rate of acute pancreatitis in a regional Australian population?

2013 ◽  
Vol 37 (2) ◽  
pp. 205
Author(s):  
Richard C. Turner ◽  
Katina D'Onise ◽  
Yan Wang
Keyword(s):  
Acute Pancreatitis ◽  
Hospital Discharge ◽  
Admission Rate ◽  
Data Sources ◽  
Case Ascertainment ◽  
Linear Modelling ◽  
Capture Recapture ◽  
Hospital Discharge Records ◽  
Log Linear ◽  
Incident Cases

Objective. Capture-recapture analysis was used to more accurately quantify the admission rate for acute pancreatitis in a regional hospital setting, in comparison to the usual method of case ascertainment. Reasons for differences in capture for the various methods were also sought. Methods. Admissions for acute pancreatitis were enumerated over a 40-month period using three data sources: hospital classification of admission diagnoses, prospective case identification, and receipt of diagnosis-specific pathology specimens. Capture-recapture analysis was applied with log-linear modelling to account for likely dependency between data sources. Covariates were noted to explain capture probability by the various data sources and for eventual stratification in the analysis process. Results. For the census period, there were 304 admissions after merging of data sources, giving a crude admission rate of 7.6 per month. Crude ascertainment rates for discharge records and prospective identification were 44% and 52% respectively. Following log-linear modelling, total admissions more than doubled to 644 (adjusted admission rate 16.1 per month). Of the covariates considered, admissions of less than three days’ duration and those occurring in December and January were significantly associated with increased capture by the hospital discharge records data source. Conclusions. In this clinical setting, admissions for acute pancreatitis are grossly underestimated by the standard case ascertainment method. The reasons for this are not clear. Hospital discharge records are nevertheless more effective than prospective case ascertainment for certain cases, such as brief admissions and those in holiday periods. What is known about the topic? Capture–recapture analysis was originally developed in animal ecology, but has since been used to estimate both prevalent and incident cases of human disease. What does this paper add? This study exposes possible deficiencies in the single-source case ascertainment methods used by most hospitals to enumerate incident cases. It is the first time that capture–recapture techniques have been used to estimate acute pancreatitis admissions. What are the implications for practitioners? To obtain accurate admissions estimates for diseases such as acute pancreatitis, capture–recapture analysis with multiple data sources is advisable. One possible solution may be to conduct intermittent prospective censuses to complement existing retrospective ascertainment methods. On a more general level, clinical staff should be better trained to provide more accurate and detailed information in case records.

Analysing Interaction Data

2010 ◽  
pp. 69-88
Author(s):  
John Stillwell ◽  
Kirk Harland
Keyword(s):  
Spatial Interaction ◽  
Interaction Model ◽  
Data Sets ◽  
Interaction Data ◽  
Interaction Variables ◽  
Movement Function ◽  
Impossible Task ◽  
Log Linear ◽  
Calibration Techniques ◽  
Modelling Methods

Large and complex interaction data sets present researchers with analytical challenges and this chapter attempts to identify and illustrate a number of ways to analyse origin-destination flows. Given the impossible task of providing a comprehensive review in such a limited space, certain analytical measures, modelling methods and visualisation techniques have been selected for inclusion, following an introduction to the notation commonly employed to represent interaction variables. Various Census and NHS patient register data sets are used to exemplify interaction measures, beginning with simple net balances and inflow/outflow ratios and moving onto indices of connectivity, inequality and distance moved. The multiplicative component framework is introduced as a particularly useful analytical approach. More sophisticated methods of modelling interaction data using statistical or mathematical calibration techniques are reviewed, examples of log-linear regression and spatial interaction model structure are highlighted in the context of historical calibration and a brief discussion of the use models for future projection is included. Maps that show patterns of geographical movement function as effective illustrative and research tools. Computerized mapping of geographical movement has evolved since the 1970s and 1980s and, in this chapter, we introduce a new method of mapping flows using vectors and illustrate this approach with micro data on pupils travelling to school. The chapter aims to provide a broad introduction to analysis methods for interaction data, many of which are subsequently applied in later chapters of the book.

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