• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.445-461
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• 2019

It is possible that data are not always fitted with sufficient precision by the existing distributions; therefore this article presents a methodology that enables the use of families of asymmetric distributions as alternative probabilistic models for survival analysis, with censorship on the right, different from those usually studied (the Exponential, Gamma, Weibull, and Lognormal distributions). We use a more flexible parametric model in terms of density behavior, assuming that data can be fit by a distribution of stable distribution families considered unconventional in the analyses of survival data that are appropriate when extreme values occur, with small probabilities that should not be ignored. In the methodology, the determination of the analytical expression of the risk function h(t) of the $L{\acute{e}}vy$ distribution is included, as it is not usually reported in the literature. A simulation was conducted to evaluate the performance of the candidate distribution when modeling survival times, including the estimation of parameters via the maximum likelihood method, survival function ${\hat{S}}$(t) and Kaplan-Meier estimator. The obtained estimates did not exhibit significant changes for different sample sizes and censorship fractions in the sample. To illustrate the usefulness of the proposed methodology, an application with real data, regarding the survival times of patients with colon cancer, was considered.

• Journal of Distribution Science
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• v.21 no.8
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• pp.11-21
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• 2023

Purpose: This study examined the effect of situational, transformational, and transactional leadership on the firm survival of restaurants distribution in Thailand during the COVID-19 pandemic. Following the existing literature, situational, transformational, and transactional leadership are the origin of firm performance leading to firm survival. Therefore, situational, transformational, and transactional leadership were the critical factors in creating the firm implementation of restaurants distribution in Thailand. Research design, data, and methodology: The sample consisted of 400 restaurants in Thailand, and the statistical approach for data analysis was an ordinary least-squares regression. The study analyzed the response bias, validity, and reliability. Results: Significantly, these findings firmly revealed that situational, transformational, and transactional leadership primarily positively affected firm performance. However, the uncertain environmental conditions had a moderate impact, resulting in a negative correlation between the three leadership styles and the company's performance. Conclusions: Despite the COVID-19 situation in Thailand, the research findings show no significant positive correlation between the performance of restaurants distribution and their survival as a business due to the COVID-19 pandemic is rare for firms to endure and survive, including restaurants distribution in Thailand. In conclusion, we have presented practical and theoretical ideas and recommendations for future research.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1829-1831
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• 2012

Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.93-109
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• 2007

In this paper we study a number of new exponentiated distributions. The survival function, failure rate and moments of the distributions have been derived using certain special functions. The behavior of the failure rate has also been studied.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.31-38
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• 2002

In the case of multiple survival times which might be censored at each covariate vector, we study the regression quantile estimations in this paper. The estimations are based on the empirical distribution functions of the censored times and the sample quantiles of the observed survival times at each covariate vector and the weighted least square method is applied for the estimation of the regression quantile. The estimators are shown to be asymptotically normally distributed under some regularity conditions.

• Journal of Periodontal and Implant Science
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• v.37 no.3
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• pp.523-534
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• 2007

This study is an analysis of types of patients and distribution of implant site and survival rate of $Xive^{(R)}$ implant. The following results on patient type, implant distribution and survival rate were compiled from 324 implant cases of 140 patients treated at the periodontal dept. of Yonsei University Hospital and G dental clinic between February 2003 and April 2006. 1. There are no dissimilarities between men and women, with patients in their 30, 40, 50s accounting for 80% of patients and accounted for 82% of implant treatments; the largest share of patients and implant treatments. 2. Mn, posterior area. accounted for 57% of implant treatments followed by Mx. posterior area(29%), Mx, anterior area(8%) and Mn, anterior area(6%). 3. Partial edentulous patients treated by single crown and bridge-type prosthesis accounted for 96% and fully edentulous patient accounted for the remaining 4%. 4. The major cause of tooth loss is periodontal disease, followed by dental canes, trauma and congenital missing. 5, The distribution of bone quality for maxillae was 54,2% for type III, followed by 30.8% for type II, 15% for type IV and 0% for type I. As for mandible, the distribution was 63% for type II, followed by 34% for type III, 2,5% for type I and 0,5% for type IV. 6. The distribution of bone quantity for maxillae was 55% for type C, followed by 35% for type B, 8% for type D and 2% for type A. As for mandible, the distribution was 60% for type B, followed by 32% for type C, 7% for type A and 0% for type D. 7. The majority of implants were those of 9.5-13 mm in length(95%) and regular diameter in width(82%). 8. The total survival rate was 98%. The survival rate was 97% in the maxillae region and 99% in the mandible region. 9. The survival rate in type I was 83%, in type II was 99%, in type III was 97% and in type IV was 100%. As for the bone quantity, the survival rate in type A and D(100%) was most, followed by type B(99%) and type C(96%). The results showed that $Xive^{(R)}$ implant could be used satisfactorily compare for the other implant system. But we most to approach carefully in certain extreme condition especially with poor bone quality and quantity.

• Journal of Environmental Science International
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• v.5 no.3
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• pp.337-346
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• 1996

The purpose of this study was to provide basic data of the growth characteristics of the landscape trees for better landscape planting design, construction and maintenance through the prediction of landscape change as time passes fly the analysis of survival rate, distribution patterns & increment percent of tree height, width, stem diameter (breast or surface) of widely used six tree species in Seongnam-si Eunhang-jugong apartment housing areas (8 years have passed after landsape alanting work). The main results can be summarized as followed. The tree survival rate of Pinus parviflora was the highest rate 89.2% than any other species, but Acer buergerianum showed the lowest survival rate at that of it 35.0%, & that of Picea abies 70.5 %, Metasequoia glyptostroboides 71.6%, Maknolia denudata 38.9%, Acer paimatum was 71.7%, As a whole, the tree survival rate of coniferous trees were relatively high. The tree height increment percent of the deciduous species wert relatively high. And that of Metasequoia glyptostroboides was the highest rate 11.61% than any other species, but that of Magnolia denudata was the lowest rate 5.59% than any other species. According to this results, the increment percent of trees in this apartment areas were comparatively lower than that of each related species planted in nursery area. And this results would be considered when landscape experts do landscape planting design, construction & maintenance. The distribution patterns of present tree size showed a Normal Distribution like any other biological features.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.179-185
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• 1994

To test the equality of survival distributions in the presence of arbitrary right censorship, the choice of weights which are functions of the number of individuals at risk at the time of each death is very important in increasing the power of the test. In this paper a weight by probit scale is derived and the efficiencies relative to the other weight's are also investigated.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.933-939
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• 2009

The bivariate data in clinical research fields often has two types of failure times, which are mark variable for the first failure time and the final failure time. This paper showed how to generate bootstrap data to get Bayesian estimation for the joint distribution of bivariate survival times. The observed data was generated by Frank's family and the fake date is simulated with the Gamma prior of survival time. The bootstrap data was obtained by combining the mimic data with the observed data and the simulated fake data from the observed data.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.325-337
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• 2017

In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.