Academic literature on the topic 'Discrete time survival analysis'

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Journal articles on the topic "Discrete time survival analysis"

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Muthén, Bengt, and Katherine Masyn. "Discrete-Time Survival Mixture Analysis." Journal of Educational and Behavioral Statistics 30, no. 1 (2005): 27–58. http://dx.doi.org/10.3102/10769986030001027.

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This article proposes a general latent variable approach to discrete-time survival analysis of nonrepeatable events such as onset of drug use. It is shown how the survival analysis can be formulated as a generalized latent class analysis of event history indicators. The latent class analysis can use covariates and can be combined with the joint modeling of other outcomes such as repeated measures for a related process. It is shown that conventional discrete-time survival analysis corresponds to a single-class latent class analysis. Multiple-class extensions are proposed, including the special cases of a class of long-term survivors and classes defined by outcomes related to survival. The estimation uses a general latent variable framework, including both categorical and continuous latent variables and incorporated in the Mplus program. Estimation is carried out using maximum likelihood via the EM algorithm. Two examples serve as illustrations. The first example concerns recidivism after incarceration in a randomized field experiment. The second example concerns school removal related to the development of aggressive behavior in the classroom.
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Kretowska, Malgorzata. "Oblique Survival Trees in Discrete Event Time Analysis." IEEE Journal of Biomedical and Health Informatics 24, no. 1 (2020): 247–58. http://dx.doi.org/10.1109/jbhi.2019.2908773.

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Jóźwiak, Katarzyna, and Mirjam Moerbeek. "Power Analysis for Trials With Discrete-Time Survival Endpoints." Journal of Educational and Behavioral Statistics 37, no. 5 (2012): 630–54. http://dx.doi.org/10.3102/1076998611424876.

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Xue, Xiaonan, and Ron Brookmeyer. "Regression analysis of discrete time survival data under heterogeneity." Statistics in Medicine 16, no. 17 (1997): 1983–93. http://dx.doi.org/10.1002/(sici)1097-0258(19970915)16:17<1983::aid-sim628>3.0.co;2-3.

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Zwick, Rebecca, and Jeffrey C. Sklar. "A Note on Standard Errors for Survival Curves in Discrete-Time Survival Analysis." Journal of Educational and Behavioral Statistics 30, no. 1 (2005): 75–92. http://dx.doi.org/10.3102/10769986030001075.

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Cox (1972) proposed a discrete-time survival model that is somewhat analogous to the proportional hazards model for continuous time. Efron (1988) showed that this model can be estimated using ordinary logistic regression software, and Singer and Willett (1993) provided a detailed illustration of a particularly flexible form of the model that includes one parameter per time period. This work has been expanded to show how logistic regression output can also be used to estimate the standard errors of the survival functions. This is particularly simple under the model described by Singer and Willett, when there are no predictors other than time.
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Barbu, Vlad, Michel Boussemart, and Nikolaos Limnios. "Discrete-Time Semi-Markov Model for Reliability and Survival Analysis." Communications in Statistics - Theory and Methods 33, no. 11 (2004): 2833–68. http://dx.doi.org/10.1081/sta-200037923.

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Moerbeek, Mirjam. "Sufficient Sample Sizes for Discrete-Time Survival Analysis Mixture Models." Structural Equation Modeling: A Multidisciplinary Journal 21, no. 1 (2014): 63–67. http://dx.doi.org/10.1080/10705511.2014.856697.

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Peugh, James, and Xitao Fan. "Identifying Unobserved Hazard Functions in Discrete-Time Survival Mixture Analysis." Structural Equation Modeling: A Multidisciplinary Journal 24, no. 1 (2016): 1–16. http://dx.doi.org/10.1080/10705511.2016.1242372.

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Singer, Judith D., and John B. Willett. "It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events." Journal of Educational Statistics 18, no. 2 (1993): 155–95. http://dx.doi.org/10.3102/10769986018002155.

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Educational researchers frequently ask whether and, if so, when events occur. Until relatively recently, however, sound statistical methods for answering such questions have not been readily available. In this article, by empirical example and mathematical argument, we demonstrate how the methods of discrete-time survival analysis provide educational statisticians with an ideal framework for studying event occurrence. Using longitudinal data on the career paths of 3,941 special educators as a springboard, we derive maximum likelihood estimators for the parameters of a discrete-time hazard model, and we show how the model can befit using standard logistic regression software. We then distinguish among the several types of main effects and interactions that can be included as predictors in the model, offering data analytic advice for the practitioner. To aid educational statisticians interested in conducting discrete-time survival analysis, we provide illustrative computer code ( SAS, 1989 ) for fitting discrete-time hazard models and for recapturing fitted hazard and survival functions.
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Moerbeek, Mirjam, and Joost Schormans. "The Effect of Discretizing Survival Times in Randomized Controlled Trials." Methodology 11, no. 2 (2015): 55–64. http://dx.doi.org/10.1027/1614-2241/a000091.

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The aim of survival analysis is to study if and when some event occurs. With continuous-time analysis subjects are followed until the time they experience the event or drop out. In practice, subjects cannot always be followed continuously and event occurrence is measured in time periods. This type of survival analysis is known as discrete-time survival analysis and measuring subjects discretely rather than continuously results in a loss of information. The aim of this paper is to study the effects of discretizing survival times for randomized controlled trials by means of a simulation study. It is shown that parameter and standard error biases of both approaches are small and those of the discrete-time approach are only slightly larger than those of the continuous-time approach. The number of time periods has a negligible effect on bias. Power levels hardly differ across the two approaches, so following subjects continuously is not necessary, except when a detailed estimate of the underlying baseline hazard function is needed.
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Dissertations / Theses on the topic "Discrete time survival analysis"

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Denson, Kathleen. "Factors Affecting Discrete-Time Survival Analysis Parameter Estimation and Model Fit Statistics." Thesis, University of North Texas, 1998. https://digital.library.unt.edu/ark:/67531/metadc278405/.

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Discrete-time survival analysis as an educational research technique has focused on analysing and interpretating parameter estimates. The purpose of this study was to examine the effects of certain data characteristics on the hazard estimates and goodness of fit statistics. Fifty-four simulated data sets were crossed with four conditions in a 2 (time period) by 3 (distribution of Y = 1) by 3 (distribution of Y = 0) by 3 (sample size) design.
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Akbayin, Bercem. "The Treatment Effect of the City Connects Intervention on Exiting Limited English Proficiency Status." Thesis, Boston College, 2017. http://hdl.handle.net/2345/bc-ir:107654.

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Thesis advisor: Henry I. Braun<br>The City Connects intervention is motivated by the belief that out-of-school factors act as barriers to student thriving in cognitive and non-cognitive domains. It seeks to address these barriers first by identifying each student’s strengths and needs and then by providing a tailored set of prevention, intervention, and enrichment programs. Underlying the program is the assumption that provision of high-quality resources and individualized services will enable children to be cognitively, socio-emotionally, and physically prepared to thrive in school. This study’s purpose was to estimate the effects of the City Connects intervention on English learners’ (EL) likelihood of exiting Limited English Proficiency (LEP) status. ELs comprise a student subpopulation most at-risk to fail academically, and exposure to the program was hypothesized to improve their likelihood of exiting LEP status earlier than otherwise. A series of one- and two-level discrete-time event history analyses were conducted on the main analytic sample as well as two sub-samples. As participation in City Connects is at the school-level, school-level matching was used for sub-samples 1 and 2, and propensity score weights were applied at the student-level for all three samples. Additionally, hazard probabilities, survival probabilities, cumulative hazard rates, and median lifetimes were estimated. Lastly, a sensitivity analysis was conducted to examine whether effects were robust to unobserved selection bias. The results indicated that ELs participating in the City Connects intervention were significantly more likely to exit LEP status earlier than their peers in comparison schools. The median time in LEP status in City Connects schools was shorter and translated into a gain of at least one half of a year in grade in mainstream classes. Also, all the fitted models indicated that approximately 10 percent more City Connects students exited LEP status by the end of fifth grade than comparison students. Findings highlight the impact of the City Connects intervention, as ELs entering mainstream classes earlier could translate into important academic and non-academic gains, such as improved academic achievement and increased self-confidence<br>Thesis (PhD) — Boston College, 2017<br>Submitted to: Boston College. Lynch School of Education<br>Discipline: Educational Research, Measurement and Evaluation
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Threatt-Milton, G. Iris. "Application of discrete time survival analysis to examine minority undergraduate retention, attrition, and persistence to graduation at selected institutions." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0010059.

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Nygren, Emma. "The effect of peacekeeping operation on conflict intensity when taking into account foreign state sponsorship : A Discrete-Time Survival Analysis." Thesis, Uppsala universitet, Institutionen för freds- och konfliktforskning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443725.

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The answer to if peacekeeping is successful or not is still debated. The focus has mostly been on internal characteristics of peacekeeping missions. While external factors, have been largely overlooked. This thesis aims to explore the effects external involvement in intrastate conflicts may have on the success of peacekeeping deployment. It poses the following research question: how does foreign state sponsorship to rebel groups affect the success of peacekeeping operations? The main argument made is that the causal mechanisms presented for why peacekeeping operations are effective, do not have an effect on the sponsors and their incentive to stop fighting. Hence, it is hypothesized that peacekeeping operations are less effective in decreasing the duration of intrastate armed conflict when rebel groups are sponsored by foreign states. The argument is tested using a discrete-time survival analysis and Cox proportional hazard models on all intrastate conflicts between 1970-2017, and foreign state sponsorship is treated as an interaction effect. The findings did not support the hypothesis but rather suggest that the presence of peacekeepers has a dominant positive conflict-intensity reducing effect. These results scratch the surface of what the effects external involvement may have on peacekeeping success and indicate that peacekeeping is successfully undermining sponsorship.
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Ye, Hong. "Comparison of Cox regression and discrete time survival models." Thesis, Wayne State University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10153426.

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<p> A standard analysis of prostate cancer biochemical failure data is done by conducting two approaches in which risk factors or covariates are measured. Cox regression and discrete-time survival models were compared under different attributes: sample size, time periods, and parameters in the model. The person-period data was reconstructed when examining the same data in discrete-time survival model. Twenty-four numerical examples covering a variety of sample sizes, time periods, and number of parameters displayed the closeness of Cox regression and discrete-time survival methods in situations typical of the cancer study. </p>
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Kim, Sunha. "A Comparison of Discrete and Continuous Survival Analysis." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/47933.

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There has been confusion in choosing a proper survival model between two popular survival models of discrete and continuous survival analysis. This study aimed to provide empirical outcomes of two survival models in educational contexts and suggest a guideline for researchers who should adopt a suitable survival model. For the model specification, the study paid attention to three factors of time metrics, censoring proportions, and sample sizes. To arrive at comprehensive understanding of the three factors, the study investigated the separate and combined effect of these factors. Furthermore, to understand the interaction mechanism of those factors, this study examined the role of the factors to determine hazard rates which have been known to cause the discrepancies between discrete and continuous survival models. To provide empirical evidence from different combinations of the factors in the use of survival analysis, this study built a series of discrete and continuous survival models using secondary data and simulated data. In the first study, using empirical data from the National Longitudinal Survey of Youth 1997 (NLSY97), this study compared analyses results from the two models having different sizes of time metrics. In the second study, by having various specifications with combination of two other factors of censoring proportions and sample sizes, this study simulated datasets to build two models and compared the analysis results. The major finding of the study is that discrete models are recommended in the conditions of large units of time metrics, low censoring proportion, or small sample sizes. Particularly, discrete model produced better outcomes for conditions with low censoring proportion (20%) and small number (i.e., four) of large time metrics (i.e., year) regardless of sample sizes. Close examination of those conditions of time metrics, censoring proportion, and sample sizes showed that the conditions resulted into high hazards (i.e., 0.20). In conclusion, to determine a proper model, it is recommended to examine hazards of each of the time units with the specific factors of time metrics, censoring proportion and sample sizes.<br>Ph. D.
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Holm, Jens Christian. "Spinors in discrete space-time." Thesis, Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/27901.

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Duchesne, Thierry. "Multiple time scales in survival analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0002/NQ44759.pdf.

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Eliiyi, Ugur. "Discrete-time Stochastic Analysis Of Land Combat." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/759472/index.pdf.

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In this study, we present the implementation and experimental analysis of a modeling approach for analyzing tactical level land combat to generate information for weapon and ammunition planning. The discrete-time stochastic model (DSM), which can handle small and moderately large force levels, is based on single shot kill probabilities. Forces are assumed to be heterogeneous on both sides, and both directed and area fire types are modeled by means of combinatorial analysis. DSM considers overkills and can handle noncombat loss and engagement processes, discrete reinforcements, force combinations and divisions. In addition to experimenting with DSM, we estimate attrition rate coefficients used in Lanchester combat models, such that the two models will yield similar figures for force levels throughout the combat.
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Rosenberg, Magdalena. "Survival Time : A Survey on the Current Survival Time for an Unprotected Public System." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-23199.

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Survival Time, what exactly does the term imply and what is the best method to measure it? Several experts within the field of Internet security have used the term; some has gone further and presented statistical facts on the survival time throughout the years. This bachelor thesis aim to present a universal definition of the term and further on measure the current survival time for a given unprotected system. By the deployment of a decoy, data will be captured and collected through port monitoring. Mainly focus will lie on building a time curve presenting the estimated time for an unprotected public system to get detected on the Internet and the elapsed time hence the system gets attacked.
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Books on the topic "Discrete time survival analysis"

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1961-, Chen Ming-Hui, and Sinha Debajyoti, eds. Bayesian survival analysis. Springer, 2001.

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Cox, D. R. Analysis of survival data. Chapman and Hall, 1990.

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Sabin, William E. Discrete-signal analysis and design. John Wiley, 2007.

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1968-, Burgess Kevin L., ed. Stability analysis of discrete event systems. Wiley, 1998.

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Fei, Zhongyang, Shuang Shi, and Peng Shi. Analysis and Synthesis for Discrete-Time Switched Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-25812-2.

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Vassiliou, P.-C. G. Discrete-time asset pricing models. ISTE Ltd/John Wiley & Sons, 2010.

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Vassiliou, P.-C. G. Discrete-time asset pricing models. ISTE Ltd/John Wiley & Sons, 2010.

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Vassiliou, P.-C. G. Discrete-time asset pricing models. ISTE Ltd/John Wiley & Sons, 2010.

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Discrete-time asset pricing models. ISTE Ltd/John Wiley & Sons, 2010.

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Discrete-event simulation: Modeling, programming, and analysis. Springer, 2001.

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Book chapters on the topic "Discrete time survival analysis"

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Masyn, Katherine E. "Discrete-Time Survival Analysis in Prevention Science." In Defining Prevention Science. Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-7424-2_22.

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Yanagimoto, Takemi. "Discrete First Passage Time Distribution for Describing Inequality among Individuals." In Lifetime Data: Models in Reliability and Survival Analysis. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-5654-8_49.

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Barbu, Vlad, and Nikolaos Limnios. "Discrete Time Semi-Markov Processes for Reliability and Survival Analysis — A Nonparametric Estimation Approach." In Statistics for Industry and Technology. Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8206-4_30.

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Carlin, John B., Rory Wolfe, Carolyn Coffey, and George C. Patton. "Survival Models: Analysis of Binary Outcomes in Longitudinal Studies Using Weighted Estimating Equations and Discrete-Time Survival Methods: Prevalence and Incidence of Smoking in An Adolescent Cohort." In Tutorials in Biostatistics. John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470023678.ch1d(ii).

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Wong, M. W. "Time-Frequency Analysis." In Discrete Fourier Analysis. Springer Basel, 2011. http://dx.doi.org/10.1007/978-3-0348-0116-4_8.

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Söderström, T. "Analysis." In Discrete-time Stochastic Systems. Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0101-7_4.

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Wong, M. W. "Time-Frequency Localized Bases." In Discrete Fourier Analysis. Springer Basel, 2011. http://dx.doi.org/10.1007/978-3-0348-0116-4_9.

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Kleinbaum, David G. "Extension of the Cox Proportional Hazards Model for Time-Dependent Variables." In Survival Analysis. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4757-2555-1_6.

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Kaiser, Gerald. "Discrete Time-Scale Analysis." In A Friendly Guide to Wavelets. Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-8111-1_6.

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Yang, Won Young. "Discrete-Time Fourier Analysis." In Signals and Systems with MATLAB. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92954-3_3.

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Conference papers on the topic "Discrete time survival analysis"

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Nguyên, Thông T., and Siu Cheung Hui. "Differentially Private Regression for Discrete-Time Survival Analysis." In CIKM '17: ACM Conference on Information and Knowledge Management. ACM, 2017. http://dx.doi.org/10.1145/3132847.3132928.

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Eleuteri, A., M. S. H. Aung, A. F. G. Taktak, B. Damato, and P. J. G. Lisboa. "Continuous and Discrete Time Survival Analysis: Neural Network Approaches." In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4353568.

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Pişkin, Erhan. "The Matter of Trade Survival." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01879.

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Besedes and Prusa (2006a-b) reveal that international trade relationships are often very short-lived contrary to previously thoughts. In line with this unexpected result, this study provides a statistical description and empirical analysis of the duration of Turkish exports. Specifically, Kaplan-Meier survival function is used to estimate the survival of trade flows over time and also a regression analysis using discrete-time duration models which allow us to properly control for unobserved heterogeneity and the presence of many tied duration times is used to explore the impact of key variables on hazard rates of export flows. The detailed trade data reported by BACI-CEPII are employed to analyze Turkey's export to European Union countries from 1998 to 2013 according to the 6-digit Harmonized system. Results obtained from the analysis of descriptive statistics suggest that the duration of Turkey’s export to European Union countries is short-lived. The median and mean duration of Turkey's exports are merely two years and 4.26, respectively. The Kaplan-Meier estimates of survival functions show that all survival curves are downward sloping with decreasing rate and about 40% of export relationships fails in the first year. The results of the discrete-time duration models indicate that product-market diversification, common language, total exports, initial value, importer GDP and lagged duration have a strong negative impact on the hazard rates of export flows. Whereas distance, common border and difference in GDP per capita have a positive effect on the hazard rates of export flows.
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Nemeth, Noel N., Osama M. Jadaan, Eric H. Baker, and John P. Gyekenyesi. "Lifetime Reliability Prediction of Ceramics Subjected to Thermal and Mechanical Cyclic Loads." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27047.

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A methodology is shown for predicting the time-dependent reliability (probability of survival) of ceramic components against catastrophic rupture when subjected to thermal and mechanical cyclic loads. This methodology is based on the Weibull distribution to model stochastic strength and a power law that models subcritical crack growth. Changes in material response that can occur with temperature or time (i.e. changing fatigue and Weibull parameters with temperature or time) are accommodated by segmenting a cycle into discrete time increments. Material properties are assumed to be constant within an increment, but can vary between increments. This capability has been added to the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. The code has been modified to have the ability to interface with commercially available finite element analysis codes such as ANSYS executed for transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.
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Ru¨de, Erich, and Rainer Hamann. "Derivation or Ship System Safety Criteria by Means of Risk-Based Ship System Safety Analysis." In ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57248.

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Nowadays an increasing popularity of alternative designs can be observed challenging the IMO Regulations of SOLAS (International Convention for the Safety Of Life At Sea). Examples are passenger ships with larger main vertical zones, novel types of survival crafts and new materials. This desire for innovative solutions combined with the society’s need for increasingly safer transport is expected to be satisfied by risk-based ship design and approval. The process of alternative ship design and arrangements, as described in MSC/Circ.1002 and MSC.1/Circ.1212, requires a risk analysis to demonstrate that the risk contribution of the novel design is less or equal to the present design. Thus the application of this process can also be regarded as risk-based design. The application of risk-based design is driven by the need for continuous improvement of the efficiency leading to lower costs for design, manufacturing or operation, because it offers the required frame for the development of new innovative solutions. IACS defines safety as absence of unacceptable levels of risk to life, limb and health. Risk is defined as a measure of likelihood that an undesirable event will occur together with a measure of the resulting consequence within a specified time, i.e., the combination of the frequency or probability and the severity of the consequence. Risk-based design involves risk assessment and risk evaluation criteria that can be defined, for instance, on basis of historical data or the ALARP process (As Low As Reasonably Practicable) combined with cost-benefit analysis. In this paper the definition of a risk evaluation criterion for systems by means of ALARP and cost-benefit analysis is presented and illustrated by a sample design of a ship fuel oil system. The risk contribution tree used for the analysis is composed of fault trees and event trees. A cost-benefit analysis is applied to establish a target system risk criterion in form of a target system failure probability. Problems related to the discrete structure of systems are discussed. The work shows that different risk analysis methods are required to describe the escalation chain from a component failure to a potential accident and its consequences.
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Olbrich, T. "AC analysis of time discrete systems." In IEE Colloquium on Analogue Simulation: the Dream and the Nightmare. IEE, 1995. http://dx.doi.org/10.1049/ic:19951201.

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Tang, Xian-ming, and Jin-shou Yu. "Stability Analysis for Discrete Time-Delay Systems." In 2008 Fourth International Conference on Networked Computing and Advanced Information Management (NCM). IEEE, 2008. http://dx.doi.org/10.1109/ncm.2008.71.

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Kharin, Yuriy. "Discrete time series: building models, statistical analysis." In Multivariate statistical analysis, econometrics and simulation of real processes. Proceedings of Xth International School-Seminar. CEMI RAS, 2020. http://dx.doi.org/10.33276/978-5-8211-0786-2-142-143.

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Guisheng Zhai, Bo Hu, K. Yasuda, and A. N. Michel. "Qualitative analysis of discrete-time switched systems." In Proceedings of 2002 American Control Conference. IEEE, 2002. http://dx.doi.org/10.1109/acc.2002.1023907.

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Perfilieva, Irina G., Nadezhda G. Yarushkina, and Tatjana V. Afanasieva. "Time series analysis by discrete F-transform." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584264.

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Reports on the topic "Discrete time survival analysis"

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Harjani, Ramesh. Design of High-Performance Survival Radios using Discrete Time Analog Signal Processing. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada547251.

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Shum, A. Discrete-Time Analysis of an ATM Multiplexer. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada302230.

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Stoffer, David S. Walsh-Fourier Analysis of Discrete-Valued Time Series. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada166139.

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Ruth, Brian G. Discrete Time Integrated Analysis Methodology for a Ground Combat System. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada366972.

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Makowski, Armand M., and Adam Shwartz. Analysis and Adaptive Control of a Discrete-Time Single-Server Network with Random Routing. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada454733.

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Duan, Jingwei, Jie Yu, Qiangrong Zhai, and Qingbian Ma. Survival and Neurologic Outcome of Different Time of Collapse to return of Spontaneous Circulation in Cardiac Arrest with Targeted Temperature Management: a Bayesian Network Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.8.0027.

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Validation of Multispectral Imaging (MSI) technology for food and feed analysis. Food Standards Agency, 2021. http://dx.doi.org/10.46756/sci.fsa.zcr161.

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Abstract:
The current testing environment for food and feed samples is complex and uses a wide variety of analytical technologies that range from chemical to PCR-based. Whilst these approaches can be deemed fit for purpose in terms of their final analytical result, they tend to be highly specialised and require considerable frontend processing to ensure that the target analyte can be reliably detected and quantified. These combined sample processing and analytical requirements typically impact on testing times and have associated cost implications that must be factored into routine testing and monitoring applications. MSI uses multiple discrete and informative wavelengths covering regions such as the UV and near infra-red spectrum to quickly determine surface colour, texture and possible chemical composition. Compared to traditional molecular biology approaches utilising DNA extraction followed by PCR-based analyses, MSI can simplify and reduce the time/costs associated with sample analysis. It is rapid and non-destructive.
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