• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.165-178
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• 2000

Bayesian methods are considered for the multiple caputure-recapture data. Reference priors are developed for such model and sampling-based approach through Gibbs sampler is used for inference from posterior distributions. Furthermore approximate Bayes factors are obtained for model selection between trap and nontrap response models. Finally one methodology is implemented for a capture-recapture model in generated data and real data.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1981-1986
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• 2015

Background: Knowledge of cancer incidences is essential for cancer prevention and control programs. Capture-recapture methods have been recommended for reducing bias and increasing the accuracy of cancer incidence estimations. This study aimed to estimate the completeness of gastric cancer registration by the capture-recapture method based on Ardabil population-based cancer registry data. Materials and Methods: All new cases of gastric cancer reported by three sources, pathology reports, death certificates and medical records that reported to Ardabil population-based cancer registry in 2006 and 2008 were enrolled in the study. The duplicate cases based on the similarity of first name, surname and fathers names were identified between sources. The estimated number of gastric cancers was calculated by the log-linear method using Stata 12 software. Results: A total of 857 new cases of gastric cancer were reported from three sources. After removing duplicates, the reported incidence rates for the years 2006 and 2008 were 35.3 and 32.5 per 100,000 population, respectively. The estimated completeness calculated by log-linear method for these years was 36.7 and 36.0, respectively. Conclusions: These results indicate that none of the sources of pathology reports, death certificates and medical records individually or collectively fully cover the incident cases of gastric cancer. We can obtain more accurate estimates of incidence rates using the capture-recapture method.

• Journal of Preventive Medicine and Public Health
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• v.33 no.3
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• pp.313-322
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• 2000

Objectives : To estimate mumps incidence during the study period and to evaluate the completeness of case reporting. Methods : Capture-recapture methods, originally developed for counting wildlife animals, were used. The data sources were 1) the National Notifiable Communicable Disease Reporting System (NNCDRS; 848 cases), 2) the School Health Reporting System, temporarily administered by the Division of Education (SHRS; 1,026 cases), and 3) a survey of students (785 cases). We estimated the number of unobserved mumps cases by matching the three data sources and fitting loglinear models to the data. We then determined the estimated total number of mumps cases by adding this to the number of observed cases. Completeness was defined as the proportion of observed cases from each source to the total of estimated cases. Results : The total number of observed cases was 1,844 and the total number of estimated cases was 1,935 (95%, CI: $1,878\sim2,070$). The overall completeness was 43.8% of the NNCDRS, 53.0% of the SHRS, and 40.6% of the survey. However, completeness varied by area and age. Conclusion : Although the completeness of NNCDRS data appeared higher than in the past, it is difficult to generalize this result In Korea, it is possible to estimate the size of health hazards relatively cheaply and quickly, by applying capture-recapture methods to various data using a multiple data collection system.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3237-3241
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• 2013

Background: Under-ascertainment and over-ascertainment are common phenomena in surveillance and registry systems of health-related events. Capture-recapture is one of the methods which is applied to determine the sensitivity of surveillance or registry systems to recognize cancer cases. This study aimed to estimate the number of cancers using data available both in the Cancer Registry Center of Northwestern Iran and in the Population-based Cancer Registry Center of Iran. Material and Methods: The studied population consisted of all cancerous cases in the northwest of Iran from 2008 to 2010. All data were extracted from two resources and entered into Microsoft Excel software. After removing common and repeat cases the data were statistically analyzed using a capture-recapture studies' specific software "CARE 1.4". Estimations were calculated by Chapman and Petersen methods with the approximate confidence interval of 95%. Results: From 2008 to 2010, the number of all cancer cases was estimated to be 21,652 (CI 95%: 19,863-22,101). Sensitivity rate of all cancer cases was 83.9% and that of Population-based Cancer Registry Center of Iran was 52%. It was 93.1% considering both resources. Conclusion: Using two resources and the capture-recapture method rather than a single resource may be a more reliable method to estimate the number of cancer cases.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.673-677
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• 2013

Introduction: Capture-recapture methods have been suggested for reducing costs of disease registration as well as reducing bias in incidence estimations. This study aimed to estimate the gastric cancer incidence in the Tehran metropolis population during 2002-2006. Materials and Methods: We investigated new cases of gastric cancer reported by three sources; death certificates, pathology reports, and medical records to Tehran population-based cancer registry during 2002-2006. $G^2$ statistics and the two-source capture-recapture method were used to select the best-fitted log-linear model and to estimate incidence, respectively. EXCEL software version 2007 and SPSS software version 16 were used for this research. Results: The number of reported cases was 4,463, with an average age of 68.5 (${\pm}12.9$) years. We found the model that combined two sources of data including pathology reports and medical records and furthermore complemented by death certificates as the best model. The reported and the estimated incidences were 11.0 and 27.1 per 100,000 respectively. Conclusions: The incidence estimated by two-source capture-recapture method is about three times higher than the incidence reported by the sources under investigation. It is recommended to move towards the implementation of population-based cancer registration using various sources of data collection to achieve more accurate data.

• Journal of Preventive Medicine and Public Health
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• v.33 no.1
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• pp.31-35
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• 2000

Objectives : This study aimed to estimate the completeness of cancer registration with Capture-recapture method. Methods : The study was conducted in the population based cancer registry of Kwangju, Korea, for which there are three main sources of notification: reports by Korean Central Cancer Registry, reports by pathology data, and the others reports by radiology data, death certificates, etc. The defined cases in three sources were matched by 13 digits Resident Register Number. To derive an estimates, log-linear models were applicated. Results : Overall completeness was estimated to be around 93%. There was some variation with age(consistently high levels below age group 60-74 years, a minimum of 88.6% above 75 years). Among the most common cancer sites, estimates of completeness were highest for thyroid cancer(97.1%), while lower estimates of completeness were derived for stomach cancer(92.3%), liver cancer(92.6%). Conclusions : Careful application of Capture-recapture method may provide an alternative to traditional approaches for estimating the completeness of cancer registration in Kwangju city.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.428-436
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• 1997

Objectives : The purpose of this paper is to estimate the completeness of the Korean Medical Insurance Data in childhood asthma. Methods : Capture-recapture method was used to estimate the prevalence of childhood asthma and case ascertainment rate(completeness) of Korean Medical Insurance Data using two source model, 'Korean Medical Insurance Committee Data (KMICD)' and 'Nationwide Study of Asthma and Allergies in Korean Children'. The asthma cases were restricted to those who were born from 1981 to 1989 and were identified by their Resident Register Number. Asthma cases in Korean Medical Insurance Data were defined as cases coded by ICD-9 493 and ICD-10 J45. In 'Nationwide Study of Asthma and Allergies in Korean Children', asthma cases were defined as the children who had been diagnosed asthma and had experienced symptoms of asthma during the past 12 months. The defined cases in two data sources were matched by 13 digits Resident Register Number. The numbers of matched patients in two data sources were 245 of 32,825 eligible total subjects. Chapman and Wittes' nearly unbiased estimation was used for capture-recapture analysis of two data sources. Results : Observed prevalence rate of childhood asthma was 5.3% and estimated prevalence rate by capture-recapture analysis was 11.6%. The highest prevalence rate was observed in 6-7 age group and the older the rate decreased. The completeness (the proportion of cases ascertained by KMICD to the total observed cases by two data sources) was 20.6%, and ranged form 10.8% to 28.8% by area. Conclusions : Invalid diagnosis of cases might overestimate the prevalence of child-hood asthma and might underestimate the completeness of Korean Medical Insurance Committee Data in this study.

• 대한예방의학회:학술대회논문집
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• 1999.10a
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• pp.62-63
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• 1999

• 대한예방의학회:학술대회논문집
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• 2002.10a
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• pp.435-436
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• 2002

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.729-748
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• 1999

In this paper we present combined estimator of capture-recapture and line transect model using bivariate detection function and detection probability according to objects being in cluster population. Here bivariate detection function use distance and cluster size. The simulation shows that combined estimator approaches the more true value the larger size parameter. Therefore this estimator using the bivariate detection function is more efficient in estimate the population size and density by size parameter.