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Journal articles on the topic 'Lexisův diagram'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Vandeschrick, Christophe. "The Lexis diagram, a misnomer." Demographic Research 4 (March 9, 2001): 97–124. http://dx.doi.org/10.4054/demres.2001.4.3.

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2

Keiding, N. "Level curves in Lexis diagrams." International Journal of Epidemiology 26, no. 2 (April 1, 1997): 462. http://dx.doi.org/10.1093/ije/26.2.462.

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3

Carstensen, B. "Age–period–cohort models for the Lexis diagram." Statistics in Medicine 26, no. 15 (2007): 3018–45. http://dx.doi.org/10.1002/sim.2764.

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4

Vandeschrick, Christophe. "Le diagramme de Lexis revisite." Population (French Edition) 47, no. 5 (September 1992): 1241. http://dx.doi.org/10.2307/1533940.

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5

Lund, Jens. "Sampling Bias in Population Studies-How to Use the Lexis Diagram." Scandinavian Journal of Statistics 27, no. 4 (December 2000): 589–604. http://dx.doi.org/10.1111/1467-9469.00210.

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6

BRUNEL, ELODIE, FABIENNE COMTE, and AGATHE GUILLOUX. "Estimation Strategies for Censored Lifetimes with a Lexis-Diagram Type Model." Scandinavian Journal of Statistics 35, no. 3 (September 2008): 557–76. http://dx.doi.org/10.1111/j.1467-9469.2007.00590.x.

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7

Brinks, Ralph, Sandra Landwehr, Rebecca Fischer-Betz, Matthias Schneider, and Guido Giani. "Lexis Diagram and Illness-Death Model: Simulating Populations in Chronic Disease Epidemiology." PLoS ONE 9, no. 9 (September 12, 2014): e106043. http://dx.doi.org/10.1371/journal.pone.0106043.

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8

Fu, Wenjiang. "Constrained Estimators and Consistency of a Regression Model on a Lexis Diagram." Journal of the American Statistical Association 111, no. 513 (January 2, 2016): 180–99. http://dx.doi.org/10.1080/01621459.2014.998761.

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9

Joo, So-Hyun, Kyung-Wook Cha, Minjeung Kim, and So-Yun Kim. "Expenditure Patterns of Korean Households between 1990 and 2018: A Lexis Diagram Analysis." Financial Planning Review 13, no. 4 (November 30, 2020): 1–38. http://dx.doi.org/10.36029/fpr.2020.11.13.4.1.

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10

Carstensen, B. "Age–period–cohort models for the Lexis diagram,Statistics in Medicine 2007;26:3018–3045." Statistics in Medicine 27, no. 9 (2008): 1561–64. http://dx.doi.org/10.1002/sim.3058.

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11

Chien, Li-Chu, Yuh-Jenn Wu, Chao A. Hsiung, Lu-Hai Wang, and I.-Shou Chang. "Smoothed Lexis Diagrams With Applications to Lung and Breast Cancer Trends in Taiwan." Journal of the American Statistical Association 110, no. 511 (July 3, 2015): 1000–1012. http://dx.doi.org/10.1080/01621459.2015.1042106.

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12

Green, Mark A., and Danny Dorling. "Visualizing the Historical and Contemporary Differences in Mortality Between the United States and Canada Using Lexis Diagrams." Canadian Journal of Public Health 103, no. 6 (November 2012): e472-e472. http://dx.doi.org/10.1007/bf03405641.

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13

Rosenbauer, Joachim, and Klaus Strassburger. "Comments on ‘Age-period-cohort models for the Lexis diagram’ by Carstensen B. Statistics in Medicine 2007; 26 :3018-3045." Statistics in Medicine 27, no. 9 (September 11, 2007): 1557–61. http://dx.doi.org/10.1002/sim.3041.

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14

Chien, Li-Hsin, Tzu-Jui Tseng, Chung-Hsing Chen, Hsin-Fang Jiang, Fang-Yu Tsai, Tsang-Wu Liu, Chao A. Hsiung, and I.-Shou Chang. "Comparison of annual percentage change in breast cancer incidence rate between Taiwan and the United States-A smoothed Lexis diagram approach." Cancer Medicine 6, no. 7 (May 31, 2017): 1762–75. http://dx.doi.org/10.1002/cam4.1102.

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15

Santos, Marco, Alexander Chakhunashvili, Anders Plantin, Kristina Westerberg, and Bo Bergman. "Exploring the use of the Lexis diagram for monitoring lead times in health care: the illustrative case of an outpatient referral process." Total Quality Management & Business Excellence 25, no. 7-8 (April 14, 2014): 876–88. http://dx.doi.org/10.1080/14783363.2014.904570.

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16

Laurenti, Ruy, and Jair Lício Ferreira Santos. "Taxa de mortalidade de menores de 5 anos proposta pela UNICEF: análise crítica de sua validade como indicador de saúde." Revista de Saúde Pública 30, no. 2 (April 1996): 148–52. http://dx.doi.org/10.1590/s0034-89101996000200006.

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Investiga-se o relacionamento entre a taxa de mortalidade de menores de cinco anos (TMM5) e os indicadores clássicos - mortalidade infantil, mortalidade de menores de 1 ano, de 1 a 4 anos, menores de cinco anos e probabilidade de óbito entre 0 e 5 anos (5q0). Do ponto de vista teórico é mostrada a equivalência entre a TMM5 e a probabilidade 5q0 da tábua de vida. Para a avaliação prática da TMM5 utilizam-se indicadores obtidos para as 24 áreas das Américas que participaram da Investigação Inter-americana de Mortalidade na Infância. A equivalência teórica entre a taxa (TMM5) e 5q0 é mostrada por meio do diagrama de Lexis. As comparações feitas através do Coeficiente de Correlação de Kendall mostram a alta concordância, principalmente entre a TMM5 e o Coeficiente de Mortalidade de menores de cinco anos e o Coeficiente de Mortalidade Infantil.

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17

Naumenko, Liudmyla, and Оksana Оliynyk. "The Cognitive Approach to Teaching Students English Terminological Lexis of the Subject Field of “Microeconomics”." PSYCHOLINGUISTICS 24, no. 2 (October 3, 2018): 236–53. http://dx.doi.org/10.31470/2309-1797-2018-24-2-236-253.

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The paper is devoted to study of prerequisites of applying cognitive approach to teaching English terminological lexis of the subject field of “microeconomics” of students of non-special higher educational establishments. Such notions as “cognition”, “memory”, “attention”, “thinking”, “intelligence” that provide student’s mental activity in the process of studying have been considered. The system of cognitive exercises on learning English economic terminology that contains seven types, i.e.: exercises on choice of proper lexical information, grouping, guesswork from the context, logic thinking, formulating scientific definitions, language game, associative thinking, problem-solving, and is based on logic operations of comparison, identification, division / disjuncture, integration / conjuncture, analysis and synthesis, deduction, abstraction, generalization, classification, typology, categorization, conceptualization, formulation of notions and judgements. The exercises have been chosen according to thematic principle (the topic “Marketing’ from the author’s manual ‘Business English Course’) and include the following kinds: identifying a key word, identifying an odd word, multiple choice, finding out a particular name, grouping the words according to their semantic combinability, guesswork from the context, formulation of definitions, solving the crossword, filling in the radial diagram of the mental map by language reactions-associations to the word ‘marketing’, problem-solving of the real-like situation dealing with marketing activity in small groups and proposing a business solution. The selected exercises develop heuristic capabilities, analytic skills, logics of thinking and creative imagination of students, facilitate memorizing, strengthen attention, intensify subject and foreign languages knowledge, help to acquire new knowledge, structure information in verbal and visual forms, motivate research activity.

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18

Parkinson, Jane, Jonathan Minton, James Lewsey, Janet Bouttell, and Gerry McCartney. "Investigation of age, period, and cohort effects to understand Scotland's excess mortality: use of Lexis diagrams and intrinsic estimator regression modelling." Lancet 390 (November 2017): S67. http://dx.doi.org/10.1016/s0140-6736(17)33002-7.

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19

Saxon, David, Alexander T. Pearson, and Peter Wu. "Hyperlink-Embedded Journal Articles Improve Statistical Knowledge and Reader Satisfaction." Journal of Graduate Medical Education 7, no. 4 (December 1, 2015): 654–57. http://dx.doi.org/10.4300/jgme-d-14-00747.1.

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ABSTRACT Background To practice evidence-based medicine, physicians should have a solid understanding of fundamental epidemiological and biostatistical concepts. Research suggests that only a minority of physicians have such an understanding of biostatistics. Objective To collect pilot data on a novel biostatistical educational tool, a hyperlink-embedded journal article, which is aimed at improving knowledge in biostatistics. Methods Forty-four physicians-in-training participated in this pilot study. Participants completed a pretest consisting of 5 questions about biostatistical terms that would be encountered in the article. They were randomized to either an unmodified journal article or to the same article with hyperlinked biostatistical terms. All participants then completed a posttest that was identical to the pretest. Results Having access to hyperlinked information had a positive association with the number of improved test answers (P = .05). Use of hyperlinks varied, and were seemingly dependent on user comfort with terms; well-understood definitions (“average”) were clicked on a few times (5.5% of participants), whereas more obscure method terms (“Lexis diagram”) were clicked on by 94% of participants. While only 42% of participants stated they would have looked up definitions of the biostatistical terms if they had not been provided in the hyperlinked article, 94% of participants identified the hyperlink tool as something they would use if readily available to them when reading journal articles. Conclusions Results of this pilot study of a novel educational intervention suggest that embedded hyperlinks within journal articles may be a useful tool to teach biostatistical terms to physicians.

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20

"Statistical inference in the Lexis diagram." Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences 332, no. 1627 (September 15, 1990): 487–509. http://dx.doi.org/10.1098/rsta.1990.0128.

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The Lexis diagram is a (time, age) coordinate system, representing individual lives by line segments of unit slope, joining (time, age) of birth and death. The main theme of this paper is non-parametric continuous-time statistical analysis on the Lexis diagram, where I indicate some possible approaches within modern survival analysis. I also introduce the history of the diagram, point processes on the diagram, and the classical statistical approach based on piecewise constant intensities. The Lexis diagram is also useful for describing morbidity, and the methodology is illustrated by two Danish studies of diabetes incidence.

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21

Dahlin, Sara. "Exploring the usefulness of Lexis diagrams for quality improvement." BMC Medical Informatics and Decision Making 20, no. 1 (January 8, 2020). http://dx.doi.org/10.1186/s12911-019-1017-3.

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Abstract Background Visualization is important to aid practitioners in understanding local care processes and drive quality improvement (QI). Important aspects include timely feedback and ability to plot data over time. Moreover, the complexity of care also needs to be understood, as it affects the variation of care processes. However, there is a lack of QI methods visualizing multiple, related factors such as diagnosis date, death date, and cause of death to unravel their complexity, which is necessary to understand processes related to survival data. Lexis diagrams visualize individual patient processes as lines and mark additional factors such as key events. This study explores the potential of Lexis diagrams to support QI through survival data analysis, focusing on feedback, timeliness, and complexity, in a gynecological cancer setting in Sweden. Methods Lexis diagrams were produced based on data from a gynecological cancer quality registry (4481 patients). The usefulness of Lexis diagrams was explored through iterative data identification and analysis through semi-structured dialogues between the researcher and domain experts (clinically active care process owners) during five meetings. Visualizations were produced and adapted by the researcher between meetings, based on the dialogues, to ensure clinical relevance, resulting in three relevant types of visualizations. Results Domain experts identified different uses depending on diagnosis group and data visualization. Key results include timely feedback through close-to-real-time visualizations, supporting discussion and understanding of trends and hypothesis-building. Visualization of care process complexity facilitated evaluation of given care. Combined visualization of individual and population levels increased patient focus and may possibly also function to motivate practitioners and management. Conclusion Lexis diagrams can aid understanding of survival data, triggering important dialogues between care givers and supporting care quality improvement and new perspectives, and can therefore complement survival curves in quality improvement.

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22

Andersson, Patrik, and Mathias Lindholm. "Mortality forecasting using a Lexis-based state-space model." Annals of Actuarial Science, September 11, 2020, 1–30. http://dx.doi.org/10.1017/s1748499520000275.

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Abstract A new method of forecasting mortality is introduced. The method is based on the continuous-time dynamics of the Lexis diagram, which given weak assumptions implies that the death count data are Poisson distributed. The underlying mortality rates are modelled with a hidden Markov model (HMM) which enables a fully likelihood-based inference. Likelihood inference is done by particle filter methods, which avoids approximating assumptions and also suggests natural model validation measures. The proposed model class contains as special cases many previous models with the important difference that the HMM methods make it possible to estimate the model efficiently. Another difference is that the population and latent variable variability can be explicitly modelled and estimated. Numerical examples show that the model performs well and that inefficient estimation methods can severely affect forecasts.

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23

Joo, So-Hyun, Kyung-Wook Cha, Min Jeung Kim, and So-Yun Kim. "한국 가계의 지출구조 변화(1990-2018): 렉시스 다이어그램 분석 (Expenditure Patterns of Korean Households between 1990 and 2018: A Lexis Diagram Analysis)." SSRN Electronic Journal, 2020. http://dx.doi.org/10.2139/ssrn.3743854.

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24

Víquez, Juan J., and Edgar A. Robles. "Revisión técnica del Estudio de Sostenibilidad del Régimen de Invalidez, Vejez y Muerte Costarricense." Revista de Ciencias Económicas 37, no. 1 (June 24, 2019). http://dx.doi.org/10.15517/rce.v37i1.37756.

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En este artículo se analizan algunas de las debilidades encontradas en el Estudio Actuarial del Régimen de Invalidez, Vejez y Muerte (IVM), realizado por el equipo de la Escuela de Matemática de la Universidad de Costa Rica (UCR). Se efectúa un análisis sobre la población económicamente activa (PEA) utilizada por ellos, y se demuestra que esta base poblacional se encuentra inicialmente subestimada, al tiempo en que se realiza una revisión del modelo, especificando algunas incoherencias demográficas que se derivan de la implementación errónea del diagrama de Lexis asociado. Posteriormente, se analizan los supuestos implícitos del modelo, los cuales afectan directamente los resultados del estudio, y se agregan posibles mejoras al modelo que devienen en un aumento de la exactitud y certeza de los resultados del informe actuarial. Como conclusión general, se estima que los resultados del estudio del IVM realizado por la UCR presentan sesgos que corresponden a un escenario pesimista.

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