• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.275-282
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• 2018

This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.

• Journal of Broadcast Engineering
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• v.12 no.1 s.34
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• pp.28-40
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• 2007

In this paper, we proposes an idea for improved sound characteristic which decreasing a problem in previous reverberation algorism structure. To later reflection sound, proposed new reverberation structure, using a lopped and nested all-pass delay line, and it is designed to improve an natural concert hall sound. In addition, In order to have best imaginary sound effect, we extracted the factors by controlling each delay line's delay time, and we realized a proposed new algorithm by using general-purpose DSP. Through several experimental cases, we observed better effect on improvement of linear flatten and reverberation density and decreasing about colorlessness and non-linear sound at previous proposed model about impulse input.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.501-510
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• 2019

This study aimed to find health related lifestyle factors that influence glycemic control for diabetes mellitus (DM) management strategies. This study used nested case-control design with matching variables that were not controlled by individuals such as age, sex, insulin or oral hypoglycemic agent (OHA) use, disease duration, education level and household income. This study analyzed 983 subjects with type 2 DM who enrolled in the $7^{th}$ (2016-2017) Korean National Health and Nutrition Examination Survey (KNHANES). The target HbA1c level of controlled glucose was defined as less than 6.5%, and 289 (30%) were achieved. Conditional multivariable logistic regression analysis was performed to find self-control factors associated with HbA1c levels. The results statistically significant for variables such as duration of diabetes, insulin or OHA use in overall cohort and body mass index (BMI), smoking and fundus Examination in matched cohort. These results are expected to provide as evidence for the intensive care criteria(disease duration, drug use) and lifestyle management strategy(BMI, smoking, fundus examination).

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.379-386
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• 2004

This paper deals with a mixed logit model for vaccination data. The effect of a newly developed vaccine for a certain chicken disease can be evaluated by a noninfection rate after injecting chicken with the disease vaccine. But there are a lot of factors that might affect the noninfecton rate. Some of these are fixed and others are random. Random factors are sometimes coming from the sampling scheme for choosing experimental units. This paper suggests a mixed model when some fixed factors need to have different experimental sizes by an experimental design and illustrates how to estimate parameters in a suggested model.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.195-202
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• 2011

The study focuses on the Repeated Measurements Design (RMD) which observations are periodically made for identical subjects within definite time periods. One of the purposes of this design is to monitor and keep track of replicated records within regular period over years. This paper also presents the classification models of RMD that is developed according to the number of factors in Between-Subject (BS) variates and Within-Subject (WS) variates. The types of models belong to each number of factors: One factor is 0BS 1WS. Two factors are 1BS 1WS and 0BS 2WS. Three factors are 1BS 2WS and 2BS 1WS. Lastly, the four factors include model of 2BS 2WS In addition, the study explains the generation mechanism of models for RMD using Generalizability Design (GD). GD is a useful method for practitioners to identify linear model of experimental design, since it generates a Venn diagram. Lastly, the research develops three types of 1BS 2WS RMDs with crossed factors and nested factors. Those are random models, mixed models and fixed models and they are presented by using Generalizability Design, $(S:A{\times}B){\times}C$. Moreover, the example of applications and its implementation steps of models developed in the study are presented for better comprehension.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1497-1500
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• 2014

Cervical cancer continues to be an important public health problem in Thailand. While the high risk human papillomavirus (HPV) types have been established as the principle causative agent of both malignancies and the precursor lesions, cervical intraepithelial neoplasia (CIN), other factors may also be involved like other sexually transmitted diseases, as well as smoking. Chlamydia trachomatis is an obligate intracellular Gramnegative bacterium which has a tendency to cause chronic infection featuring inflammation and therefore might be expected to increase the risk of cervical cancer. In the present nested case-control study, 61 cases of cervical cancer and 288 matched controls with original serum samples were identified from the Khon Kaen Cohort, established in the North-East of Thailand, by linkage to the Khon Kaen population based cancer registry. C. trachomatis specific IgG antibodies at recruitment were measured by microimmunofluorescence and assessed for association with cervical cancer using STATA release10. No significant link was noted either with all cancers or after removal of adenocarcinomas. The results suggest no association between Chlamydia infection and cervical cancer development in North-East Thailand, but possible influencing factors must be considered in any future research on this topic.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.1035-1046
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• 2015

Variance components models incorporate various random factors in the form of linear models. There are two experimental Layouts for the classification of factors under variance components models: nested classification and crossed classification. We consider two-way variance components models and investigate the effect of experimental Layout on the performance of model selection criteria AIC and BIC. The effect of experimental Layout is studied through a simulation study with various combinations of parameters in a systematic fashion. The simulation study shows differences in performance of model selection methods between the two classification. There is a particular tendency to prefer the smaller model than the true model when the variance component of a nested factor becomes relatively larger than a nesting factor that is persistent even when the sample size is not small.

• Parasites, Hosts and Diseases
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• v.57 no.3
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• pp.233-242
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• 2019

Detailed description of malaria in low transmission areas is crucial for elimination. The current study aimed to provide a comprehensive description for malaria transmission in Jazan, a low transmission district, southwestern Saudi Arabia. Patients at a tertiary care hospital were recruited in our study between August 2016 and September 2018. Malaria diagnosis was performed through a species-specific nested polymerase chain reaction (nested PCR), microscopy and Paramax-$3^{TM}$ rapid detection test (RDT). Malaria was detected in 30 patients by the PCR, with point prevalence of 10.9%. Of these malaria infections, 80% was imported, 26.6% was asymptomatic and 23.3% was sub-microscopic. Malaria was reported throughout the year, with February/March and September/October peaks. Infection was significantly more in males than in females (P=0.01). Likewise, infections were detected more in febrile than in non-febrile patients (P=0.01). Adult aged 15-24 years, fever and travel were identified as high-risk factors. Malaria was primarily attributed to Plasmodium falciparum mono-infections, followed by P. vivax mono-infections and lastly to falciparum/vivax mixed infections accounting 76.6%, 16.6%, and 6.6% of PCR-confirmed malaria cases, respectively. The nested PCR was superior to the smear microscopy (sensitivity 76.6%; specificity 100%) and the RDT (sensitivity 83.3%, specificity 94.2%). The overall percent agreement between microscopy and the RDT was 92.7% (kappa=0.63). High proportion of imported malaria including sub-microscopic and sub-patent cases were described. We suggest that incorporation of molecular tool into the conventional malaria diagnosis is beneficial in Jazan district.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.205-214
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• 1996

As flexible Bayesian test criteria for nested point null hypotheses of multiple regression coefficients, partial and overall Bayes factors are introduced under a class of intuitively meaningful prior. The criteria lead to a simple method for considering different prior beliefs on the subspaces that constitute a partition of the coefficient parameter space. A couple of tests are suggested based on the criteria. It is shown that they enable us to obtain pairwise comparisons of hypotheses of the partitioned subspaces. Through a Monte Carlo simulation, performance of the tests based on the criteria are compared with the usual Bayesian test (based on Bayes factor)in terms of their respective powers.