Relevant bibliographies by topics / Dynamic propensity score matching

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dynamic propensity score matching'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Dynamic propensity score matching"

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Ríos, José, Joaquín Saez-Peñataro, Caridad Pontes, and Ferran Torres. "Is Propensity Score Analysis a Valid Surrogate of Randomization for the Avoidance of Allocation Bias?" Seminars in Liver Disease 37, no. 03 (2017): 275–86. http://dx.doi.org/10.1055/s-0037-1606213.

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AbstractRandomized clinical trials are the gold standard when experimental designs are feasible. Randomization allows the handling of allocation bias for known and unknown confounders. Specific tools such as blocking, stratification, and dynamic allocation provide additional guarantees to simple randomization. When an experimental design is not feasible, the propensity score (PS) has been shown to produce greater benefit than traditional methods (i.e., restriction, stratification, matching and adjusting). There appears to be a hierarchy in terms of the effectiveness of balancing for PS techniq
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Strawiński, Paweł. "An improvement of quality of statistical matching for survey data using dynamic caliper." Statistics in Transition new series 12, no. 3 (2011): 595–607. http://dx.doi.org/10.59170/stattrans-2011-045.

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Nowadays, matching is a widely used technique to estimate program net effects. The goal of the method is to establish a counterfactual state by choosing from the control pool a group that is similar to those in the treatment group. In this article we propose a modification of the matching with caliper procedure. The novelty in our approach is setting the caliper value as a fraction of estimated propensity score. The simulation results and examples are presented. Using Deheija and Wahba (1999) data benefits of the proposed approach are stressed. The obtained results indicate that proposed appro
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Ho, Thanh, Sarana Shinkuma, and Koji Shimada. "The Effects of Dynamic Pricing of Electric Power on Consumer Behavior: A Propensity Score Analysis for Empirical Study on Nushima Island, Japan." Energies 11, no. 8 (2018): 2175. http://dx.doi.org/10.3390/en11082175.

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This study aimed to investigate the change of consumer behavior in electric power consumption after the application of dynamic pricing via real-time feedback. Afield experiment of dynamic pricing was carried out on Nushima Island, which is located in Hyogo Prefecture in central Japan. The panel data of hourly electric power consumption among 50 households (including 22 control households and 28 treated households) were collected from a baseline survey (14 days before the dynamic pricing experiment was conducted) and during the 14-day experimental period. Propensity score analysis with local li
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Bondonio, Daniele, and Robert T. Greenbaum. "Natural disasters and relief assistance: Empirical evidence on the resilience of U.S. counties using dynamic propensity score matching." Journal of Regional Science 58, no. 3 (2018): 659–80. http://dx.doi.org/10.1111/jors.12379.

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Liu, Yan-Qing, Hui Li, Jie-Rui Liu, and Yan-Song Lin. "UNFAVORABLE RESPONSES TO RADIOIODINE THERAPY IN N1B PAPILLARY THYROID CANCER: A PROPENSITY SCORE MATCHING STUDY." Endocrine Practice 25, no. 12 (2019): 1286–94. http://dx.doi.org/10.4158/ep-2019-0155.

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Objective: Regional nodal metastases carry prognostic significance in papillary thyroid cancer (PTC). However, whether different locational nodal metastases correlate with different therapeutic responses remains controversial. We innovatively applied the response to therapy restratification system to evaluate the dynamic disease status after surgery and radioactive iodine (RAI) therapy in PTC patients with different locational nodal metastases. Methods: A total of 585 nondistant-metastatic PTC patients who underwent total thyroidectomy and RAI therapy were retrospectively enrolled. Patients wi
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Zhang, Chaofei, Zhanghua Xu, Yuanyao Yang, Lei Sun, and Haitao Li. "Dynamic Monitoring of Ecological Quality in Eastern Ukraine Amidst the Russia‐Ukraine Conflict." Photogrammetric Engineering & Remote Sensing 90, no. 7 (2024): 427–35. http://dx.doi.org/10.14358/pers.23-00085r2.

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To evaluate the spatiotemporal changes in the ecological environment of eastern Ukraine since the Russia-Ukraine conflict, this study used MODIS images from March to September 2020 and 2022 to calculate the Remote Sensing???Based Ecological Index. In 2022, compared with 2020, conflict zones exhibited reduced improvement and increased slight degradation, whereas nonconflict areas showed marginal enhancement. Through propensity score matching, the research confirmed the causal relationship between conflict and ecological trends. Pathway analysis revealed that the conflict contributed to 0.016 un
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Huang, Juanjuan, Jinhong Jiang, and Qishui Chi. "The Impact of New Rural Cooperative Insurance on Migrant Workers' Consumption: Empirical Analysis Based on China Migrants Dynamic Survey." Research in World Economy 11, no. 3 (2020): 36. http://dx.doi.org/10.5430/rwe.v11n3p36.

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Based on the data from the National Health Commission of China, this paper analyzes the impact of the new rural cooperative medical insurance on the household consumption of migrant workers by using the ordinary least squares method and the propensity score matching method. The study found that the average annual per capita consumption of participating migrant workers decreased by 3.5%, and the influence of NCMS on the consumption of different groups of migrant workers was significantly different, among which, the negative impact of consumption of low-income group, young group and group with h
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Zhang, Guan-Yu, Rong Guan, and Hui-Juan Wang. "The Nonlinear Causal Relationship Between Environmental Regulation and Technological Innovation—Evidence Based on the Generalized Propensity Score Matching Method." Sustainability 12, no. 1 (2020): 352. http://dx.doi.org/10.3390/su12010352.

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The existing research on testing Porter’s hypothesis has not considered the selective bias in the sample when establishing a model. However, the selective bias is likely to cause instability of estimation results and reduce the reference value of conclusions. This article, based on individual enterprises in the China Industrial Enterprise Database, aims to verify the selective bias existing in previous research. Then, using the generalized propensity score matching method, a frontier method in the field of causal inference, we re-examined the causal relationship between environmental regulatio
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Zhang, Tianjie, Donglei Wang, and Yang Lu. "A Dynamic Spatiotemporal Understanding of Changes in Social Vulnerability to Wildfires at Local Scale." Fire 7, no. 7 (2024): 251. http://dx.doi.org/10.3390/fire7070251.

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Research on wildfires and social vulnerability has gained significant importance due to the increasing frequency and severity of wildfires around the world. This study investigates the dynamic changes in social vulnerability to wildfires over a decade in Idaho, USA, utilizing GIS-based tools and a quasi-experimental design. We assess the evolving nature of social vulnerability at a local scale, emphasizing both spatial and temporal dynamics. Initially, we identified social vulnerability trends in relation to varying levels of wildfire risk. The research then employs propensity score matching t
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Goodwin, Kelly, Emin Aghayev, Hans-Joachim Riesner, Ralph Greiner-Perth, and Kathrin Bieri. "Dynamic Posterior Stabilization versus Posterior Lumbar Intervertebral Fusion: A Matched Cohort Study Based on the Spine Tango Registry." Journal of Neurological Surgery Part A: Central European Neurosurgery 79, no. 03 (2018): 224–30. http://dx.doi.org/10.1055/s-0037-1615264.

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Purpose The primary aim of dynamic stabilization is to stabilize the spine and preserve function without overstressing adjacent segments, which is a potential risk of fusion surgery. However, direct comparative analyses of the two approaches are still limited, and little is known about the association of patient-reported outcomes with these treatment options. Objective To compare the clinical outcomes of dynamic posterior stabilization using the DSS Stabilization System (Paradigm Spine, LLC, New York, New York, United States) versus posterior lumbar intervertebral fusion (PLIF) based on data f
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Dissertations / Theses on the topic "Dynamic propensity score matching"

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Alvarez, Rodrigo Baggi Prieto. "Instrumentos públicos de incentivo às exportações e desempenho de estreantes no mercado internacional." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/96/96131/tde-25092013-160818/.

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A compreensão da dinâmica de persistência e evasão da atividade exportadora é fundamental para o desenho de incentivos adequados às firmas estreantes no mercado internacional e encontra respaldo nos modelos da nova teoria do comércio internacional. O propósito deste trabalho é investigar os determinantes do desempenho de firmas industriais brasileiras estreantes no mercado internacional, em termos de probabilidade de sobrevivência e evolução do valor exportado, com especial atenção aos impactos dos instrumentos de apoio Drawback, BNDES Exim e Proex. Para tanto, serão analisadas empresas estrea
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Granlund, David. "Economic policy in health care : Sickness absence and pharmaceutical costs." Doctoral thesis, Umeå : Department of Economics, Umeå University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1137.

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Oelrich, Oscar. "Causal Inference Using Propensity Score Matching in Clustered Data." Thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-225990.

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Propensity score matching is commonly used to estimate causal effects of treatments. However, when using data with a hierarchical structure, we need to take the multilevel nature of the data into account. In this thesis the estimation of propensity scores with multilevel models is presented to extend propensity score matching for use with multilevel data. A Monte Carlo simulation study is performed to evaluate several different estimators. It is shown that propensity score estimators ignoring the multilevel structure of the data are biased, while fixed effects models produce unbiased results.
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Picchio, Matteo. "Temporary jobs in Italy: wage differentials and their dynamics." Doctoral thesis, Università Politecnica delle Marche, 2007. http://hdl.handle.net/11566/242638.

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Gli obiettivi di questa tesi sono l'analisi degli effetti salariali del lavoro temporaneo in Italia e la stima dinamica della probabilità di essere un lavoratore temporaneo, utilizzando l'Indagine sui bilanci delle famiglie italiane (SHIW) condotta dalla Banca d'Italia. Il primo di questi è affrontato utilizzando differenti tecniche econometriche: il punto di partenza è un'analisi cross-section utilizzando l'ondata del 2002 della SHIW; dopodiché, sfruttando le ondate del 2000 e del 2002 della SHIW e quindi la dimensione longitudinale, un'analisi econometrica panel è condotta. Infine, facendo r
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Li, Chih-Lin. "Propensity Score Matching in Observational Studies with Multiple Time Points." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313420291.

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Acharya, Sunayan. "AN INVESTIGATION INTO LONG-RUN ABNORMAL RETURNS USING PROPENSITY SCORE MATCHING." UKnowledge, 2012. http://uknowledge.uky.edu/busadmin_etds/2.

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This is a study in two parts. In part-1, I identify several methods of estimating long-run abnormal returns prevalent in the finance literature and present an alternative using propensity score matching. I first demonstrate the concept with a simple simulation using generated data. I then employ historical returns from CRSP and randomly select events from the dataset using various alternating criteria. I test the efficacy of different methods in terms of type-I and type-II errors in detecting abnormal returns over 12- 36- and 60- month periods. I use various forms of propensity score matching:
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Pufahl, Andrea, and Christoph Weiss. "Evaluating the effects of farm programs. Results from propensity score matching." Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, 2007. http://epub.wu.ac.at/1486/1/document.pdf.

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The paper applies a non-parametric propensity score matching approach to evaluate the effects of two types of farm programs (agri-environment (AE) programs and the less favoured area (LFA) scheme) on input use and farm output of individual farms in Germany. The analysis reveals a positive and significant treatment effect of the LFA scheme for farm sales and the area under cultivation. Participants in AE schemes are found to significantly increase the area under cultivation (in particular grassland), resulting in a decrease of livestock densities. Furthermore, participation in AE programs signi
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Xie, Diqiong. "Bias and variance of treatment effect estimators using propensity-score matching." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/4980.

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Observational studies are an indispensable complement to randomized clinical trials (RCT) for comparison of treatment effectiveness. Often RCTs cannot be carried out due to the costs of the trial, ethical questions and rarity of the outcome. When noncompliance and missing data are prevalent, RCTs become more like observational studies. The main problem is to adjust for the selection bias in the observational study. One increasingly used method is propensity-score matching. Compared to traditional multi-covariate matching methods, matching on the propensity score alleviates the curse of dimensi
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Sanchez, Blanca Nidia Aquino. "Emigração no Paraguai: efeitos das remessas." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/96/96131/tde-26092011-105040/.

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Neste trabalho analisou-se o impacto das remessas financeiras sobre os patrimônios dos ativos nos domicílios, no país de origem. Utilizamos dados da Encuesta Permanente de Hogares de 2008, os quais foram fornecidos pelo órgão Dirección General de Estadística, Encuestas y Censos do Paraguai. Com estes dados realizamos uma comparação entre os domicílios com e sem remessas, independente de terem ou não emigrantes. A metodologia utilizada para realizar a comparação foi o Propensity Score Matching (PSM) com dois algoritmos, Vizinhos Próximos e Kernel. Os patrimônios dos ativos são carros, aluguéis
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Waernbaum, Ingeborg. "Covariate selection and propensity score specification in causal inference." Doctoral thesis, Umeå : Umeå universitet, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1688.

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Books on the topic "Dynamic propensity score matching"

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Dehejia, Rajeev H. Propensity score matching methods for non-experimental causal studies. National Bureau of Economic Research, 1998.

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Caliendo, Marco. Some practical guidance for the implementation of propensity score matching. IZA, 2005.

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Essama-Nssah, B. Propensity score matching and policy impact analysis - a demonstration in eviews. World Bank, 2006.

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Shapiro, Joseph. Compensatory education for disadvantaged Mexican students: An impact evaluation using propensity score matching. World Bank, 2004.

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Heckman, James J. A note on adapting propensity score matching and selection models to choice based samples. National Bureau of Economic Research, 2009.

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Heckman, James J. A note on adapting propensity score matching and selection models to choice based samples. National Bureau of Economic Research, 2009.

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Kate, Wilkinson, and University of Cape Town. Southern Africa Labour and Development Research Unit, eds. Assessing the incidence of public works programmes: Using propensity score matching techniques to assess the poverty targeting of employment in two public works programmes in South Africa. Southern Africa Labour and Development Research Unit, University of Cape Town, 2009.

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Strawiński, Paweł. Propensity Score Matching. Własności. Warsaw University Press, 2014. http://dx.doi.org/10.31338/uw.9788323516965.

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Cintina, Inna, and Inessa Love. Re-Evaluating Microfinance: Evidence from Propensity Score Matching. World Bank, Washington, DC, 2017. http://dx.doi.org/10.1596/1813-9450-8028.

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Cintina, Inna, and Inessa Love. Re-evaluating Microfinance: Evidence from Propensity Score Matching. Published by Oxford University Press on behalf of the World Bank, 2019. http://dx.doi.org/10.1596/34290.

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Book chapters on the topic "Dynamic propensity score matching"

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Propensity Score Matching." In Statistics Applied to Clinical Studies. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2863-9_29.

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Grunwald, Ben, and John M. MacDonald. "Propensity Score Matching." In Encyclopedia of Criminology and Criminal Justice. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-5690-2_46.

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Weisburd, David, David B. Wilson, Alese Wooditch, and Chester Britt. "Propensity Score Matching." In Advanced Statistics in Criminology and Criminal Justice. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67738-1_10.

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Moscarelli, Marco. "Propensity Score Matching." In Biostatistics With 'R': A Guide for Medical Doctors. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-33073-5_12.

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Rosenbaum, Paul R. "Propensity Score." In Handbook of Matching and Weighting Adjustments for Causal Inference. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003102670-2.

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Imai, Kosuke, and Yang Ning. "Covariate Balancing Propensity Score." In Handbook of Matching and Weighting Adjustments for Causal Inference. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003102670-15.

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Percoco, Marco. "Propensity Score Matching: When Units Meet." In SpringerBriefs in Regional Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09519-6_3.

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Lu, Bo, and Stanley Lemeshow. "Survey Sampling and Propensity Score Matching." In The Wiley Handbook of Psychometric Testing. John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781118489772.ch4.

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Sweeten, Gary. "Propensity Score Matching and Prevention Science." In Preventing Crime and Violence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44124-5_17.

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Böhlen, Michael H., Oksana Dolmatova, Michael Krauthammer, Alphonse Mariyagnanaseelan, Jonathan Stahl, and Timo Surbeck. "Iterations for Propensity Score Matching in MonetDB." In Advances in Databases and Information Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54832-2_15.

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Conference papers on the topic "Dynamic propensity score matching"

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Dominic, Nicholas, and Bens Pardamean. "Mitigating Berkson's Paradox with Neural Propensity Score Matching in E-Commerce Deals." In 2024 6th International Conference on Cybernetics and Intelligent System (ICORIS). IEEE, 2024. https://doi.org/10.1109/icoris63540.2024.10903875.

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Chen, Kaidi, Xuexia Liang, Yuhua Mo, Yuankun Li, Liangben Xu, and Weili Kong. "A Retail Product Prediction Model Incorporating Machine Learning and Propensity Score Matching Method." In 2024 7th International Conference on Computer Information Science and Application Technology (CISAT). IEEE, 2024. http://dx.doi.org/10.1109/cisat62382.2024.10695432.

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Wu, Zeyu, Yuuki Nishiyama, and Yuya Shibuya. "The Bidirectional Relationship between Emotional Change and Physical Movement Activities: An Analysis Using Propensity Score Matching Methods." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825918.

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(Randy) Nixon, Robert A. "Conducting Precast Concrete Cylinder Pipe Condition Assessment by Matching Corrosion Damage Mechanisms to Diagnostic Methods." In CONFERENCE 2022. AMPP, 2022. https://doi.org/10.5006/c2022-18234.

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Abstract Precast concrete cylinder pipe (PCCP) has been widely used successfully for both water transmission and wastewater force mains for many decades. In the case of water conveyance, the majority of failures occur due to soil side deterioration. This includes chloride intrusion and low pH soils and ground water promoting corrosion of the prestressed wires. High sulfate bearing ground waters can also cause expansive degradation of the cement mortar coating exposing the prestressed wires to corrosive conditions. Internal corrosion rarely results in PCCP failure in potable water conveyance. I
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Karimi, Hamid, Muhammad Fawad Akbar Khan, Haochen Liu, Tyler Derr, and Hui Liu. "Enhancing Individual Fairness through Propensity Score Matching." In 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2022. http://dx.doi.org/10.1109/dsaa54385.2022.10032333.

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Charkhabi, Masoud. "Adjustments to propensity score matching for network structures." In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921651.

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Tsunoda, Masateru, and Sousuke Amasaki. "On Software Productivity Analysis with Propensity Score Matching." In 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 2017. http://dx.doi.org/10.1109/esem.2017.59.

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Sun, Xiaogeng. "Using Propensity Score Matching to Find Comparison Schools." In 2021 AERA Annual Meeting. AERA, 2021. http://dx.doi.org/10.3102/1692823.

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Liu, Yuchu, David Issa Mattos, Jan Bosch, Helena Holmstrom Olsson, and Jonn Lantz. "Bayesian propensity score matching in automotive embedded software engineering." In 2021 28th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2021. http://dx.doi.org/10.1109/apsec53868.2021.00031.

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Rivera, William A., Amit Goel, and J. Peter Kincaid. "OUPS: A Combined Approach Using SMOTE and Propensity Score Matching." In 2014 13th International Conference on Machine Learning and Applications (ICMLA). IEEE, 2014. http://dx.doi.org/10.1109/icmla.2014.106.

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Reports on the topic "Dynamic propensity score matching"

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Heinrich, Carolyn. Demand and Supply-Side Determinants of Conditional Cash Transfer Program Effectiveness: Improving the First-Generation Programs. Inter-American Development Bank, 2005. http://dx.doi.org/10.18235/0011174.

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The Programa Nacional de Becas Estudiantiles is a conditional cash transfer program designed to promote long-term human capital accumulation among Argentine youth and to reduce poverty. This study follows a 1999 cohort of students from 24 schools for five years. Propensity score matching methods are used with a comparison group of students who were excluded due to quotas to estimate the average and marginal impacts of the Becas program. Multilevel methods are also used to estimate the contributions of Becas program management and school characteristics in explaining variation between schools i
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Abadie, Alberto, and Guido Imbens. Matching on the Estimated Propensity Score. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w15301.

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Sianesi, Barbara. Propensity score matching and causal inference. The IFS, 2009. http://dx.doi.org/10.1920/ps.ifs.2024.1048.

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Maffioli, Alessandro, Carolyn Heinrich, and Gonzalo Vázquez. A Primer for Applying Propensity-Score Matching. Inter-American Development Bank, 2010. http://dx.doi.org/10.18235/0008567.

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This document provides a guide to the key aspects of implementing Propensity-Score Matching (PSM) methodology. It summarizes the basic conditions under which PSM can be used to estimate the impact of a program and the data required, presenting examples of PSM applications. It explains how the Conditional Independence Assumption, combined with the Overlap Condition, reduces selection bias when participation in a program is determined by observable characteristics. It also describes different matching algorithms and some tests to assess the quality of the matching.
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Dehejia, Rajeev, and Sadek Wahba. Propensity Score Matching Methods for Non-experimental Causal Studies. National Bureau of Economic Research, 1998. http://dx.doi.org/10.3386/w6829.

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Mocan, H. Naci, and Erdal Tekin. Catholic Schools and Bad Behavior: A Propensity Score Matching Analysis. National Bureau of Economic Research, 2002. http://dx.doi.org/10.3386/w9172.

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Heckman, James, and Petra Todd. A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w15179.

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Aedo, Cristían, and Sergio Nuñez. The Impact of Training Policies in Latin America and the Caribbean: The Case of Programa Joven. Inter-American Development Bank, 2004. http://dx.doi.org/10.18235/0011253.

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This paper evaluates Programa Joven, a training program conducted by Argentina's Ministerio del Trabajo. The paper adapts and applies a non-experimental evaluation methodology to answer the following questions: (1) Did Programa Joven increase the labor income of the trainees? (2) Did Programa Joven increase the probability of employment? (3) What was the rate of return to dollars spent on Programa Joven? The basic methodology used was the Matching Estimators approach. The application of this methodology requires two steps: first, the estimation of a model of program participation (propensity s
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Augsburg, Britta. Econometric evaluation of the SEWA Bank in India: applying matching techniques based on the propensity score. The IFS, 2006. http://dx.doi.org/10.1920/re.ifs.2024.0736.

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Díaz, Juan José, and Sudhanshu Handa. An Assessment of Propensity Score Matching as a Non Experimental Impact Estimator: Evidence from Mexico's PROGRESA Program. Inter-American Development Bank, 2005. http://dx.doi.org/10.18235/0011170.

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In this working paper the authors present evidence on the reliability of propensity score matching to estimate the bias associated with the effect of treatment on the treated, exploiting the availability of experimental data from a Mexican antipoverty program (PROGRESA: Programa de Educación, Salud y Alimentación). The data comes from several outcomes such as food expenditure and child schooling and labor. The methodology compares the results of the experimental impact estimator with those using matched samples drawn from a (non-experimental) national survey carried out to measure household in
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