ResearchPad - Accounting https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Panel Dataset of Ethical Commitment Disclosures in Malaysia]]> https://www.researchpad.co/product?articleinfo=N7a48c7c0-efb8-4adb-9d33-3e94a0c9e849 <![CDATA[Datasets for corporate governance index of Jordanian non-financial sector firms]]> https://www.researchpad.co/product?articleinfo=N0cbed61a-d15d-49f9-9c44-24b6087678fa

This article covers comprehensive data on firm-level corporate governance practices as imposed by the Jordan Securities Commission (JSC). The study includes panel data for 95 non-financial Jordanian listed firms (industrial and service sector) in Amman Stock Exchange (ASE). The time frame used for this study is from 2012 to 2017. Data presented were extracted from the annual reports of each firm. The annual reports had been downloaded from the official website of the ASE. The data can be used easily by the researcher to develop and calculate a corporate governance index that involves thirty-two internal governance attributes and is comprised of three equally weighted sub-indices. The first sub-index which is “Disclosure and Transparency” consists of 15 unique attributes. While the second sub-index, “Board Effectiveness and Composition” consists of 9 unique attributes. The last sub-index which is “Shareholders Rights” consists of 8 unique attributes. Thus, the un-weighted corporate governance index has an important feature that is easily replicated and modified, enabling the researcher to rate firms based on an aggregate index score or by using the sub-indices score also.

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<![CDATA[Data on the potential of nutrition-information apps from a consumer behaviour perspective]]> https://www.researchpad.co/product?articleinfo=N611f0b55-9dc9-4b11-898f-3afe59db61cd

This paper presents data on the influence of the use of a nutrition-information app (Edo) on healthy eating. The methodology adopted included a baseline (t0) and a follow-up online questionnaire (t1). The first survey was sent to 7000 consumers who had already downloaded the app. This survey collected data on users’ perceived healthiness of their own diet, food purchasing habits, sociodemographic information, concern for appearance, perception of the Health Belief Model constructs, and objective and perceived healthy food knowledge. The follow-up survey (t1) was sent to the respondents who had used the app for 12 weeks. It collected data on app satisfaction, recommended additional app features, consumers’ perception on the Health Belief Model constructs, and consumers’ objective and perceived healthy food knowledge. Data elaboration included two factor analyses elaboration, one for t0 data and one for t1 data. The aim was the identification of constructs as latent factors of the data. The value of each construct was calculated and compared between t0 and t1. The data presented in this article can help the replication of studies about similar apps and enhance the cooperation among app developers, consumer behaviour scientists, nutritionists and marketing experts for apps development. For conclusion and interpretation of data, the original article can be consulted (DOI:10.1016/j.foodres.2019.108766).

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<![CDATA[Dataset for understanding why people share their travel experiences on social media: Structural equation model analysis]]> https://www.researchpad.co/product?articleinfo=N2f383dac-4af3-4187-9f1b-0cfb3f96cdca

The data presented in this article relates to the individual intrinsic and extrinsic motivations to share travel experience in social media. The 381 records were gathered in Portugal using an online survey. A statistical analysis of the data was carried out using partial least squares (PLS). This dataset shows a relationship between identification, internalization, and compliance to perceived enjoyment, and also, between perceived enjoyment, altruistic motivations, personal fulfillment, and self-actualization as well as security and privacy reasons to actual travel experience sharing. For further findings and interpretation, please refer to the research article entitled “Why do people share their travel experiences on social media?” [1]. We suggest the use of this data to compare with data collected by other researchers to develop cross-country analyses based on the model proposed by Oliveira, Araujo, and Tam [1].

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<![CDATA[Multilevel assessment of restaurant profitability: Evidence with European data]]> https://www.researchpad.co/product?articleinfo=N7cfd33ef-5e13-4ee0-ae5f-de6b98b7f882

Previous literature has analysed the effects of establishment regressors on different measures of restaurant financial performance [1,2]. However, as [3] stated, these studies have focused on the analysis at establishment level rather than at corporate level. Determining the factors that explain the restaurant profitability is not only an important phenomenon for establishments but also for companies because they adapt their products, services and strategies to obtain additional benefits and cash flow [1]. Additionally, progressive globalization has forced companies to operate in countries with environments that differ from the companies’ country of origin [4]. In this context, the dataset presented in this paper sought to contribute to the existing literature in two ways. First, it allows us to investigate the factors that determine the profitability of restaurant corporations using advanced measures of financial performance. Second, a multilevel experimental design may be helpful when understanding country heterogeneity in companies´ profitability. The dataset contains a sample of 860 restaurant corporations operating in 18 European countries. From each corporation in the sample 6 financial variables were collected, and from each country, 10 context variables associated with economic conditions and tourism environment were considered. Due to the lack of data that allow a global analysis of the factors that determine profitability in the restaurant industry, this dataset can play an important role for business management, which should control not only their financial ratios but also the macroeconomic conditions and tourism environment where the companies operate.

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<![CDATA[Real estate announcements monitoring dataset for Latvia 2018]]> https://www.researchpad.co/product?articleinfo=Nc0c77550-b24b-47d8-a0cf-5512b795573a

The dataset represents a collection of real estate announcements published in 2018 in the Latvian leading advertisement website www.ss.com [1]. In the Latvian case, mentioned advertisement website is alternative information source in contrast with several (5–7) large real estate agencies. The mentioned advertisement website has no important competitors in Latvia, closer competitor reklama. lv [2] is 4–5 times smaller. Advertisement website www.ss.com represents information from small and medium size agencies, as well from individuals, who want to take part in the real estate market. The collected dataset reflects the observation dynamics of 12 months during 2018, including in total 238 thousand observations. Dataset has 24 dimensions, such as in announcement mentioned price for real estate, deal types, dimensions of location of real estate, such as region, district, address; characteristics of real estate, such as real estate type (land, flat and so on), size and main characteristics for each real estate type, such as land area or bad rooms in apartments. The dataset is hosted in Data Archiving and Networked Services (DANS) repository [3].

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<![CDATA[Dataset for holiday rentals’ daily rate pricing in a cultural tourism destination]]> https://www.researchpad.co/product?articleinfo=Nd790d9dc-2494-48bb-9753-a9821875187d

This data article describes a holiday rental dataset from a medium-size cultural city destination. Daily rate and variables related to location, size, amenities, rating, and seasonality are highlighted as the main features. The data was extracted from Booking.com, legal registration of the accommodation (RTA) and Google Maps, among other sources. This dataset contains data from 665 holiday rentals offered as entire flat (rent per room was discarded), with a total of 1623 cases and 28 variables considered. Regarding data extraction, RTA is ordered by registration number, which is taken and, through a Google search with the following structure: “apartment registration no. + Booking + Seville”, the holiday rental profile in Booking.com is found. Then, it is verified that both the address of the accommodation and the registration number match in RTA and Booking.com, proceeding with data extraction to a Microsoft Excel's file. Google Maps is used to determine the minutes spent walking from the accommodation to the spot of maximum tourist interest of the city. A price index based on the average price per square meter of real estate per district is also incorporated to the dataset, as well as a visual appeal rating made by the authors of every holiday rental based on its Booking.com photos profile. Only cases with complete data were considered. A statistics summary of all variables of the data collected is presented. This dataset can be used to develop an estimation model of daily prices of stay in holiday rentals through predetermined variables. Econometrics methodologies applied to this dataset can also allow testing which variables included affecting the composition of holiday rentals' daily rates and which not, as well as determining their respective influence on daily rates.

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<![CDATA[Code and data on the categorization of soft-drink bottles using image silhouettes]]> https://www.researchpad.co/product?articleinfo=5c50f662d5eed0c48462c4e0

This data article includes the visual stimuli used to test the categorization of a set of soft drink bottle silhouettes. Additionally, subjects’ perceptual categorization was associated with each visual stimuli. The silhouette of the soft drink bottles was characterized by calculating the most common object shape measurements such as width, height and area and combining them with more complex and specific quantitative shape measurements such as the principal moment statistics. Finally, this data article includes the code for extracting these shape characteristics from image silhouettes. For interpretation and discussion, please see the original article entitled “Quantitative analysis of product categorization in soft drinks using bottle silhouettes” (Arboled and Arce-Lopera, 2015) [1].

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<![CDATA[Hotel booking demand datasets]]> https://www.researchpad.co/product?articleinfo=5c26b492d5eed0c484763527

This data article describes two datasets with hotel demand data. One of the hotels (H1) is a resort hotel and the other is a city hotel (H2). Both datasets share the same structure, with 31 variables describing the 40,060 observations of H1 and 79,330 observations of H2. Each observation represents a hotel booking. Both datasets comprehend bookings due to arrive between the 1st of July of 2015 and the 31st of August 2017, including bookings that effectively arrived and bookings that were canceled. Since this is hotel real data, all data elements pertaining hotel or costumer identification were deleted. Due to the scarcity of real business data for scientific and educational purposes, these datasets can have an important role for research and education in revenue management, machine learning, or data mining, as well as in other fields.

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<![CDATA[An integrated dataset on organisational retention attributes and commitment of selected ICT and accounting firms]]> https://www.researchpad.co/product?articleinfo=5b5abf0b463d7e0e3ef9376f

The article presented an integrated data on organisational retention strategies and commitment of selected ICT and Accounting firms in Nigeria. The study adopted a quantitative approach with a survey research design to establish the major determinants of employee retention strategies. The population of this study included staff and management of the selected firms. Data was analysed with the use of structural equation modelling and the field data set is made widely accessible to enable critical or a more comprehensive investigation. The findings identified critical attraction factors for the retention of sampled firms. It was recommended that ICT firms will need to adopt consistent range of strategies to attract and retain people with the right ICT skills, in the right place and at the right time.

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<![CDATA[Data on the role of leadership in developing expertise in teaching in developing country]]> https://www.researchpad.co/product?articleinfo=5b5ab756463d7e0d8745f157

This article has researched role of leaders in developing expertise in teaching and their influence on teachers in secondary school in Kazakhstan. Also, how principles can affect to educators developing to meet needs and challenges of today's trends of teaching and learning. The following research report has been precisely written to evaluate the exact role of leadership practices in the development of expertise in teaching and in what manner the expert teachers or the principals help to develop expertise across various departments of the schools.

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<![CDATA[An evaluation framework for comparing geocoding systems]]> https://www.researchpad.co/product?articleinfo=5989daeeab0ee8fa60bc03dc

Background

Geocoding, the process of converting textual information describing a location into one or more digital geographic representations, is a routine task performed at large organizations and government agencies across the globe. In a health context, this task is often a fundamental first step performed prior to all operations that take place in a spatially-based health study. As such, the quality of the geocoding system used within these agencies is of paramount concern to the agency (the producer) and researchers or policy-makers who wish to use these data (consumers). However, geocoding systems are continually evolving with new products coming on the market continuously. Agencies must develop and use criteria across a number axes when faced with decisions about building, buying, or maintaining any particular geocoding systems. To date, published criteria have focused on one or more aspects of geocode quality without taking a holistic view of a geocoding system’s role within a large organization. The primary purpose of this study is to develop and test an evaluation framework to assist a large organization in determining which geocoding systems will meet its operational needs.

Methods

A geocoding platform evaluation framework is derived through an examination of prior literature on geocoding accuracy. The framework developed extends commonly used geocoding metrics to take into account the specific concerns of large organizations for which geocoding is a fundamental operational capability tightly-knit into its core mission of processing health data records. A case study is performed to evaluate the strengths and weaknesses of five geocoding platforms currently available in the Australian geospatial marketplace.

Results

The evaluation framework developed in this research is proven successful in differentiating between key capabilities of geocoding systems that are important in the context of a large organization with significant investments in geocoding resources. Results from the proposed methodology highlight important differences across all axes of geocoding system comparisons including spatial data output accuracy, reference data coverage, system flexibility, the potential for tight integration, and the need for specialized staff and/or development time and funding. Such results can empower decisions-makers within large organizations as they make decisions and investments in geocoding systems.

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<![CDATA[Characteristics of residential areas and transportational walking among frail and non-frail Dutch elderly: does the size of the area matter?]]> https://www.researchpad.co/product?articleinfo=5989dab3ab0ee8fa60bac1d6

Background

A residential area supportive for walking may facilitate elderly to live longer independently. However, current evidence on area characteristics potentially important for walking among older persons is mixed. This study hypothesized that the importance of area characteristics for transportational walking depends on the size of the area characteristics measured, and older person’s frailty level.

Methods

The study population consisted of 408 Dutch community-dwelling persons aged 65 years and older participating in the Elderly And their Neighborhood (ELANE) study in 2011–2012. Characteristics (aesthetics, functional features, safety, and destinations) of areas surrounding participants’ residences ranging from a buffer of 400 meters up to 1600 meters (based on walking path networks) were linked with self-reported transportational walking using linear regression analyses. In addition, interaction effects between frailty level and area characteristics were tested.

Results

An increase in functional features (e.g. presence of sidewalks and benches) within a 400 meter buffer, in aesthetics (e.g. absence of litter and graffiti) within 800 and 1200 meter buffers, and an increase of one destination per buffer of 400 and 800 meters were associated with more transportational walking, up to 2.89 minutes per two weeks (CI 1.07-7.32; p < 0.05). No differences were found between frail and non-frail elderly.

Conclusions

Better functional and aesthetic features, and more destinations in the residential area of community-dwelling older persons were associated with more transportational walking. The importance of area characteristics for transportational walking differs by area size, but not by frailty level. Neighbourhood improvements may increase transportational walking among older persons, thereby contributing to living longer independently.

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<![CDATA[Utility of passive photography to objectively audit built environment features of active transport journeys: an observational study]]> https://www.researchpad.co/product?articleinfo=5989da78ab0ee8fa60b975f6

Background

Active transport can contribute to physical activity accumulation and improved health in adults. The built environment is an established associate of active transport behaviours; however, assessment of environmental features encountered during journeys remains challenging. The purpose of this study was to examine the utility of wearable cameras to objectively audit and quantify environmental features along work-related walking and cycling routes.

Methods

A convenience sample of employed adults was recruited in New Zealand, in June 2011. Participants wore a SenseCam for all journeys over three weekdays and completed travel diaries and demographic questionnaires. SenseCam images for work-related active transport journeys were coded for presence of environmental features hypothesised to be related to active transport. Differences in presence of features by transport mode and in participant-reported and SenseCam-derived journey duration were determined using two-sample tests of proportion and an independent samples t-test, respectively.

Results

Fifteen adults participated in the study, yielding 1749 SenseCam images from 30 work-related active transport journeys for coding. Significant differences in presence of features were found between walking and cycling journeys. Almost a quarter of images were uncodeable due to being too dark to determine features. There was a non-significant tendency for respondents to under-report their journey duration.

Conclusion

This study provides proof of concept for the use of the SenseCam to capture built environment data in real time that may be related to active transportation. Further work is required to test and refine coding methodologies across a range of settings, travel behaviours, and demographic groups.

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<![CDATA[An objective index of walkability for research and planning in the Sydney Metropolitan Region of New South Wales, Australia: an ecological study]]> https://www.researchpad.co/product?articleinfo=5989da00ab0ee8fa60b73df4

Background

Walkability describes the capacity of the built environment to support walking for various purposes. This paper describes the construction and validation of two objective walkability indexes for Sydney, Australia.

Methods

Walkability indexes using residential density, intersection density, land use mix, with and without retail floor area ratio were calculated for 5,858 Sydney Census Collection Districts in a geographical information system. Associations between variables were evaluated using Spearman’s rho (ρ). Internal consistency and factor structure of indexes were estimated with Cronbach’s alpha and principal components analysis; convergent and predictive validity were measured using weighted kappa (κw) and by comparison with reported walking to work at the 2006 Australian Census using logistic regression. Spatial variation in walkability was assessed using choropleth maps and Moran’s I.

Results

A three-attribute abridged Sydney Walkability Index comprising residential density, intersection density and land use mix was constructed for all Sydney as retail floor area was only available for 5.3% of Census Collection Districts. A four-attribute full index including retail floor area ratio was calculated for 263 Census Collection Districts in the Sydney Central Business District. Abridged and full walkability index scores for these 263 areas were strongly correlated (ρ=0.93) and there was good agreement between walkability quartiles (κw=0.73). Internal consistency ranged from 0.60 to 0.71, and all index variables loaded highly on a single factor. The percentage of employed persons who walked to work increased with increasing walkability: 3.0% in low income-low walkability areas versus 7.9% in low income-high walkability areas; and 2.1% in high income-low walkability areas versus 11% in high income-high walkability areas. The adjusted odds of walking to work were 1.05 (0.96–1.15), 1.58 (1.45–1.71) and 3.02 (2.76–3.30) times higher in medium, high and very high compared to low walkability areas. Associations were similar for full and abridged indexes.

Conclusions

The abridged Sydney Walkability Index has predictive validity for utilitarian walking, will inform urban planning in Sydney, and will be used as an objective measure of neighbourhood walkability in a large population cohort. Abridged walkability indexes may be useful in settings where retail floor area data are unavailable.

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<![CDATA[GIS-aided planning of insecticide spraying to control dengue transmission]]> https://www.researchpad.co/product?articleinfo=5989dacbab0ee8fa60bb4158

Background

The purpose of this paper is to integrate a multi-objective integer programming formulation and geographic information system (GIS) into dynamically planning the insecticide spraying area for preventing the transmission of dengue fever.

Methods

The optimal spraying area to combat dengue infections is calculated by the multi-objective integer programming model using the dengue epidemic in 2007 in Tainan City of southern Taiwan and is compared with the areas actually sprayed by the local health department. The dynamic epidemic indicators (i.e. frequency, intensity and duration) that identify major temporal characteristics of the dynamic process of an epidemic are all incorporated into the model.

Results

The results indicate that the model can design the spraying area effectively when the trade-off between the coverage of dengue epidemics risk and area compactness is considered.

Conclusions

The model provides an alternative way to obtain a cost-effective spraying area in controlling future dengue epidemics. The proposed model in this study will be beneficial for strategically allocating dengue control resources.

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<![CDATA[A linear programming model for preserving privacy when disclosing patient spatial information for secondary purposes]]> https://www.researchpad.co/product?articleinfo=5989da74ab0ee8fa60b95ee7

Background

A linear programming (LP) model was proposed to create de-identified data sets that maximally include spatial detail (e.g., geocodes such as ZIP or postal codes, census blocks, and locations on maps) while complying with the HIPAA Privacy Rule’s Expert Determination method, i.e., ensuring that the risk of re-identification is very small. The LP model determines the transition probability from an original location of a patient to a new randomized location. However, it has a limitation for the cases of areas with a small population (e.g., median of 10 people in a ZIP code).

Methods

We extend the previous LP model to accommodate the cases of a smaller population in some locations, while creating de-identified patient spatial data sets which ensure the risk of re-identification is very small.

Results

Our LP model was applied to a data set of 11,740 postal codes in the City of Ottawa, Canada. On this data set we demonstrated the limitations of the previous LP model, in that it produces improbable results, and showed how our extensions to deal with small areas allows the de-identification of the whole data set.

Conclusions

The LP model described in this study can be used to de-identify geospatial information for areas with small populations with minimal distortion to postal codes. Our LP model can be extended to include other information, such as age and gender.

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<![CDATA[Spatial autocorrelation in uptake of antenatal care and relationship to individual, household and village-level factors: results from a community-based survey of pregnant women in six districts in western Kenya]]> https://www.researchpad.co/product?articleinfo=5989da75ab0ee8fa60b96546

Background

The majority of maternal deaths, stillbirths, and neonatal deaths are concentrated in a few countries, many of which have weak health systems, poor access to health services, and low coverage of key health interventions. Early and consistent antenatal care (ANC) attendance could significantly reduce maternal and neonatal morbidity and mortality. Despite this, most Kenyan mothers initiate ANC care late in pregnancy and attend fewer than the recommended visits.

Methods

We used survey data from 6,200 pregnant women across six districts in western Kenya to understand demand-side factors related to use of ANC. Bayesian multi-level models were developed to explore the relative importance of individual, household and village-level factors in relation to ANC use.

Results

There is significant spatial autocorrelation of ANC attendance in three of the six districts and considerable heterogeneity in factors related to ANC use between districts. Working outside the home limited ANC attendance. Maternal age, the number of small children in the household, and ownership of livestock were important in some districts, but not all. Village proportions of pregnancy in women of child-bearing age was significantly correlated to ANC use in three of the six districts. Geographic distance to health facilities and the type of nearest facility was not correlated with ANC use. After incorporating individual, household and village-level covariates, no residual spatial autocorrelation remained in the outcome.

Conclusions

ANC attendance was consistently low across all the districts, but factors related to poor attendance varied. This heterogeneity is expected for an outcome that is highly influenced by socio-cultural values and local context. Interventions to improve use of ANC must be tailored to local context and should include explicit approaches to reach women who work outside the home.

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<![CDATA[Using simple agent-based modeling to inform and enhance neighborhood walkability]]> https://www.researchpad.co/product?articleinfo=5989dacdab0ee8fa60bb4d4f

Background

Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate.

Methods

This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input.

Results

The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections.

Conclusions

The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) ‘learning’ and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).

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<![CDATA[Spatial heterogeneity of type I error for local cluster detection tests]]> https://www.researchpad.co/product?articleinfo=5989db02ab0ee8fa60bc7008

Background

Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect.

Methods

A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect.

Results

The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated.

Conclusions

In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance.

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