• Journal of Veterinary Clinics
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• v.28 no.1
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• pp.101-107
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• 2011

This study aimed to determine dose-response (DR) curve of avian influenza (AI) virus to predict the probability of illness or adverse health effects that may result from exposure to a pathogenic microorganism in a quantitative microbial risk assessment. To determine the parametric DR relationship of several strains of AI virus, 7 feeding trial data sets challenging humans (5 sets) and chickens (2 sets) for strains of H3N2 (4 sets), H5N1 (2 sets) and H1N1 (1 set) from the published literatures. Except for one data set (study with intra-tracheal inoculation for data set no. 6), all were obtained from the studies with intranasal inoculation. The data were analyzed using three types of DR model as the basis of heterogeneity in infectivity of AI strains in humans and chickens: exponential, beta-binomial and beta-Poisson. We fitted to the data using maximum likelihood estimation to get the parameter estimates of each model. The alpha and beta values of the beta-Poisson DR model ranged 0.06-0.19 and 1.7-48.8, respectively for H3N2 strain. Corresponding values for H5N1 ranged 0.464-0.563 and 97.3-99.4, respectively. For H1N1 the parameter values were 0.103 and 12.7, respectively. Using the exponential model, r (infectivity parameter) ranged from $1.6{\times}10^{-8}$ to $1.2{\times}10^{-5}$ for H3N2 and from $7.5{\times}10^{-3}$ to $4.0{\times}10^{-2}$ for H5N1, while the value was $1.6{\times}10^{-8}$ for H1N1. The beta-Poisson DR model provided the best fit to five of 7 data sets tested, and the estimated parameter values in betabinomial model were very close to those of beta-Poisson. Our study indicated that beta-binomial or beta-Poisson model could be the choice for DR modeling of AI, even though DR relationship varied depending on the virus strains studied, as indicated in prior studies. Further DR modeling should be conducted to quantify the differences among AI virus strains.

• Korean journal of applied entomology
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• v.55 no.4
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• pp.405-412
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• 2016

Infestation of adults and pupae of sweetpotato whitefly, Bemisia tabaci, on paprika (Capsicum annuum var. angulosum) grown in greenhouses in Jinju, Gyeongnam province during 2014was determined by counts of the number of target stage of B. tabaci per leaflet. Binomial sampling plans were developed based on the relationship between the mean density per leaflet (m) and the proportion of leaflets infested with less than T whiteflies ($P_T$), according to the empirical model $(({\ln}(m)={\alpha}+{\beta}({\ln}(-{\ln}(1-P_T))))$. T was defined as the tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaflet in this study. Increasing the sample size, regardless of tally threshold, had little effect on the precision of the binomial sampling plan. Based on the precision of the model, T = 1 was chosen as the best tally threshold for estimating densities of B. tabaci adults and T = 3 was best tally threshold in B. tabaci pupae. Using the results obtained in the greenhouse, a simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) demonstrated the plan's validity. Above all, the binomial model with T = 1 and T = 3 provided reliable predictions of the mean densities of B. tabaci adults and pupae on greenhouse paprika.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.41-52
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• 1993

In this paper we study numerical behavior of the adjustments for the variances of the pearson and deviance type dispersion statistics in two overdispersed mixture models; negative binomial and beta-binomial distribution. They are important families of an extended quasi-likelihood model which is very useful for the joint modelling of mean and dispersion. Comparisons are done for two types of dispersion statistics for various mean and dispersion parameters by simulation studies.

• Korean journal of applied entomology
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• v.37 no.2
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• pp.151-157
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• 1998

Infestations of two spotted spider mite (TSSM), Tetranychus urticae Koch, on glasshouse rose (Rosa sp.) grown by an arching method, were determined by counts of the number of TSSM per leaflet in Buyeo, Chungnam Province, for a 2-yr period. Binomial sampling plans were developed based on the relationship between mean density per leaflet (m), and proportion of leaflets infested with ( T mites (PT), according to the empirical model In (m) = a+p In (-ln (1 -PT)). T was defined as tally threshold, and set to 1, 3, 5, 7, and 9 mites per leaflet. Increasing sample size had little effects on the precision of the binomial sampling plan, regardless of tally threshold. However, the precision increased with higher tally thresholds. There was a negligible improvement in precision with T ) 7 mites per leaflet. T= 7 was chosen as the best tally threshold for estimating densities of TSSM based on the precision of the model. Independent data set was used to evaluate the model. The binomial model with T= 7 provided reliable predictions of mean densities of TSSM observed on the commercial glasshouse roses.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.341-352
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• 2003

Collecting data through experiment, the observers are an import source of measurement error and the inference on the measure of agreement, say kappa, is necessary. The models commonly used are complicated general mixture model, which have many nuisance parameters. Orthogonalization of parameters reduce the effect of nuisance parameter. Orthogonalization of estimating function gives the same effect as the parameter orthogonalization. In this study, the method for orthogonalization of estimating equation is studied and applied to the Beta-binomial model to examine the properties of the estimate of kappa. As a result, the likelihood function is insensitive to the change of the nuisance parameter and bias is smaller than the result of m.1.e. when kappa has extreme values

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.81-95
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• 2008

In this paper, the negative Polya-Eggenberger distribution has been introduced by compounding negative binomial distribution with beta distribution of I-kind which generates a number of univariate contagious or compound (or mixture of) distributions as its particular cases. The distribution is unimode, over dispersed and all of its positive and negative integer moments exist. The difference equation of the proposed model shows that it is a member of the Ord's family of distribution. Some of its interesting properties have been explored besides different methods of estimation been discussed. Finally, the parameters of the proposed model have been estimated by using a computer programme in R-software. Application of the proposed model to some data, available in the literature, has been given and its goodness of fit demonstrated.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2841-2852
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• 2018

This study examines regression modeling method using zero-inflated distribution in relation to estimation of exposure distribution required in advertisement media planning. Exposure distribution is the percentage of audiences that are exposed each time the ad is repeated. Such an exposure distribution plays a very important role in providing basic information necessary for calculating various indicators for quantitatively measuring the advertising effect. Especially, due to the decrease of advertising price and the spread of various media, the frequency of the advertisement or the broadcasting of specific advertisements has been greatly increased compared to the past. As a result, the frequency of exposure is relatively decreasing. In this situation, the number of individuals who are not exposed to the media, that is, are not exposed to advertising structurally is increasing. This research proposes advertising exposure distribution models using a zero-inflated regression model, and conducts a comparative study using actual cases.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.121-150
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• 2003

The National Health Interview Survey (NHIS) is one of the surveys used to assess the health status of the US population. One indicator of the nation's health is the total number of doctor visits made by the household members in the past year, There is a substantial nonresponse among the sampled households, and the main issue we address here is that the nonrespones mechanism should not be ignored because respondents and nonrespondents differ. It is standard practice to summarize the number of doctor visits by the binary variable of no doctor visit versus at least one doctor visit by a household for each of the fifty states and the District of Columbia. We consider a nonignorable nonresponse model that expresses uncertainty about ignorability through the ratio of odds of a household doctor visit among respondents to the odds of doctor visit among all households. This is a hierarchical model in which a nonignorable nonresponse model is centered on an ignorable nonresponse model. Another feature of this model is that it permits us to "borrow strength" across states as in small area estimation; this helps because some of the parameters are weakly identified. However, for simplicity we assume that the hyperparameters are fixed but unknown, and these hyperparameters are estimated by the EM algorithm; thereby making our method Bayes empirical Bayes. Our main result is that for some of the states the nonresponse mechanism can be considered non-ignorable, and that 95% credible intervals of the probability of a household doctor visit and the probability that a household responds shed important light on the NHIS.

• Korean journal of applied entomology
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• v.48 no.1
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• pp.45-51
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• 2009

This paper presents sequential sampling plans for evaluating the pest density based on complete counts from probe in a rice storage warehouse. Both maize weevil and Indian meal moth population showed negative binomial dispersion patterns in brown rice storage. For cost-effective monitoring and action decision making system, sequential sampling plans by using the sequential probability ratio test (SPRT) were developed for the maize weevil and Indian meal moth in warehouses with 0.8 M/T storage bags. The action threshold for the two insect pests was estimated to 5 insects per kg, which was projected by a matrix model. The results show that, using SPRT methods, managers can make decisions using only 20 probe with a minimum risk of incorrect assessment.

• Korean Journal of Radiology
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• v.24 no.10
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• pp.996-1005
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• 2023

Objective: To compare the incidence of aspiration pneumonia, nausea, and vomiting after intravascular administration of nonionic iodinated contrast media (ICM) between patients who fasted before contrast injection and those who did not. Materials and Methods: Ovid-MEDLINE and Embase databases were searched from their inception dates until September 2022 to identify original articles that met the following criteria: 1) randomized controlled trials or observational studies, 2) separate reports of the incidence of aspiration pneumonia, nausea, and vomiting after intravascular injection of non-ionic ICM, and 3) inclusion of patients undergoing radiological examinations without fasting. A bivariate beta-binomial model was used to compare the risk difference in adverse events between fasting and non-fasting groups. The I² statistic was used to assess heterogeneity across the studies. Results: Ten studies, encompassing 308013 patients (non-fasting, 158442), were included in this meta-analysis. No cases of aspiration pneumonia were reported. The pooled incidence of nausea was 4.6% (95% confidence interval [CI]: 1.4%, 7.8%) in the fasting group and 4.6% (95% CI: 1.1%, 8.1%) in the non-fasting group. The pooled incidence of vomiting was 2.1% (95% CI: 0.0%, 4.2%) in the fasting group and 2.5% (95% CI: 0.7%, 4.2%) in the non-fasting group. The risk difference (incidence in the non-fasting group-incidence in the fasting group) in the incidence of nausea and vomiting was 0.0% (95% CI: -4.7%, 4.7%) and 0.4% (95% CI: -2.3%, 3.1%), respectively. Heterogeneity between the studies was low (I² = 0%-13.5%). Conclusion: Lack of fasting before intravascular administration of non-ionic ICM for radiological examinations did not increase the risk of emetic complications significantly. This finding suggests that hospitals can relax fasting policies without compromising patient safety.