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Relevant bibliographies by topics / Statistical significance

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Academic literature on the topic 'Statistical significance'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Statistical significance"

1

Mahuli, AmitVasant, and SimpyAmit Mahuli. "Significance of statistical significance." Journal of Dental Research and Review 2, no. 3 (2015): 106. http://dx.doi.org/10.4103/2348-2915.169828.

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Yohannessen Vásquez, Karla, Sergio Alvarado Orellana, and Valentina Vergara Villarroel. "Significancia clínica y significancia estadística. ¿Qué es más significativo?" Neumología pediátrica 19, no. 2 (2024): 41–45. http://dx.doi.org/10.51451/np.v19i2.583.

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Una de las dificultades más comunes que enfrentan los lectores de artículos del área de la biomedicina y epidemiología es la interpretación del término “significativo”. El término “estadísticamente significativo” a menudo se malinterpreta como un resultado “clínicamente significativo”. La confusión surge del hecho de que muchas personas equiparan “significativo” con su significado literal de “importante”, sin embargo, la significación estadística cuantifica la probabilidad de que los resultados de un estudio se deban al azar, mientras que la significancia clínica refleja la importancia práctic

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Ziegel, Eric R., and Siu Chow. "Statistical Significance." Technometrics 41, no. 2 (1999): 181. http://dx.doi.org/10.2307/1270759.

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Cox, D. R. "Statistical Significance." Annual Review of Statistics and Its Application 7, no. 1 (2020): 1–10. http://dx.doi.org/10.1146/annurev-statistics-031219-041051.

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A broad review is given of the role of statistical significance tests in the analysis of empirical data. Four main types of application are outlined. The first, conceptually quite different from the others, concerns decision making in such contexts as medical screening and industrial inspection. The others assess the security of conclusions. The article concludes with an outline discussion of some more specialized points.

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Mirsky, Steve. "Statistical Significance." Scientific American 310, no. 5 (2014): 80. http://dx.doi.org/10.1038/scientificamerican0514-80.

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Ranstam, Jonas. "Statistical significance." Acta Radiologica 49, no. 2 (2008): 220–21. http://dx.doi.org/10.1080/02841850801924256.

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Sedgwick, P. "Clinical significance versus statistical significance." BMJ 348, mar14 11 (2014): g2130. http://dx.doi.org/10.1136/bmj.g2130.

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Rosen, Brittany L., and Andrea L. DeMaria. "Statistical Significance vs. Practical Significance." American Journal of Health Education 43, no. 4 (2012): 235–41. http://dx.doi.org/10.1080/19325037.2012.10599241.

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Curtiss, Frederic R. "Statistical Significance Versus Practical Significance." Journal of Managed Care Pharmacy 8, no. 5 (2002): 404. http://dx.doi.org/10.18553/jmcp.2002.8.5.404.

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Mariani, Alessandro Wasum, and Paulo Manuel Pêgo-Fernandes. "Statistical significance and clinical significance." Sao Paulo Medical Journal 132, no. 2 (2014): 71–72. http://dx.doi.org/10.1590/1516-3180.2014.1322817.

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Dissertations / Theses on the topic "Statistical significance"

1

Agrawal, Ankit. "Sequence-specific sequence comparison using pairwise statistical significance." [Ames, Iowa : Iowa State University], 2009.

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2

Lybrand, Blythe, Ginette Blackhart, Amanda Parish, and Hannah Lowe. "Investigating the Misrepresentation of Statistical Significance in Empirical Articles." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/honors/646.

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In an attempt to preserve research integrity, the aim of this study is to examine how often statistical results are being misrepresented in empirical studies by using terms such as “marginally significant,” “approached significance,” or “trend toward significance” when interpreting findings. The use of these terms gives ambiguous significance to results that are in fact nonsignificant, which threatens future research by contributing to issues such as the replication crisis. For this study, data were coded from 437 empirical articles published online in The Journal of Personality and Social Psy

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Price, Carly S., and L. Lee Glenn. "Statistical Significance of Eating Disorders and Adverse Perinatal Outcomes." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etsu-works/7462.

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Excerpt: The study by Linna et al1 posited that “eating disorders appear to be associated with several adverse perinatal outcomes, particularly in offspring.” The adverse outcomes included anemia, slow fetal growth, premature contractions, and perinatal death. However, this conclusion cannot be supported by the data because the authors failed to correct the standard value of P = .05 to account for the large number of hypothesis tests. This leads to what is known as type 2 error and causes a hypothesis to be accepted that is actually false.

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Guo, Junhai. "Statistical significance and biological relevance of microarray data clustering." Cincinnati, Ohio : University of Cincinnati, 2008. http://rave.ohiolink.edu/etdc/view.cgi?acc_num=ucin1204736862.

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Karki, Rabindra. "Regulation of glucose metabolism by Alox8." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1507.

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Type II diabetes is one of the leading cause of morbidity in the U.S. and other parts of the world. Insulin resistance which precedes Type II diabetes is a complex state of the body where the body fails to respond to insulin. Its complexity lies in its multifactorial origin that is to say various environmental and polygenic components come into play. Here we try to dissect one of these components - `Alox8' in transgenic mice and try to see if it affects blood glucose homeostasis. Comparison of glucose tolerance and insulin sensitivity among sixteen mice comprising of six wild type, five hetero

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Morrison, Chelsea L., and L. Lee Glenn. "Statistical Significance of Paracetamol Administration in Fetal and Maternal Body Temperatures." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/etsu-works/7470.

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Excerpt: In their recent study [ 1 ], Lavesson et al. concluded, “In febrile parturients, neither maternal nor fetal temperatures dropped after paracetamol, but paracetamol halted an increasing trend and stabilized the fetal temperature. The effect of paracetamol on maternal temperature was inconclusive”. This conclusion, however, is not supported by the data in the study, in that the calculation of case and control temperature differences demonstrates clear fetal and maternal temperature decreases after paracetamol.

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Zumbo, Bruno Domenico 1966 Carleton University Dissertation Psychology. "Statistical methods to overcome nonindependence of coupled data in significance testing." Ottawa.:, 1992.

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Tanaka, Emi. "Statistical Methods for Improving Motif Evaluation." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13922.

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Gene regulation, especially cis-regulation of gene expression by the binding of transcription factors, is a critical component of cellular physiology. Transcription regulation is heavily influenced by the binding of transcription factors, and as such, it is of great interest to characterise these binding sites. The binding sites of a transcription factor are collectively referred to as a regulatory motif. Recent advancement in sequencing technology generated vast amounts of biological data. Thus computational tools are required to process and analyse this massive information. In particular, c

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Dallas, C. "The significance of costume on classical Attic grave stelai : A statistical analysis." Thesis, University of Oxford, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381837.

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Castellano, Escuder Pol. "Statistical methods for intake prediction and biological significance analysis in nutrimetabolomic studies." Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/673827.

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This thesis is the product of three and a half years working on the complex world of metabolomics and nutrition. All the work presented here is focussed on the problems arising from associating and integrating metabolomics data with nutritional or dietary data. This issue has been approached using both observational and interventional studies and from a mainly bioinformatic point of view, proposing different methods and tools to reduce the complexity of nutrimetabolomics data analysis. Thus, this work consists of four chapters divided into three parts, in addition to a summ

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Books on the topic "Statistical significance"

1

Mohr, Lawerence B. Understanding significance testing. Sage Publications, 1990.

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Toyoda, Hideki. Statistical Significance and the PHC Curve. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7748-8.

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Cookson, Hazel. Assessing the statistical significance of rare events. Directorate of Psychological Services, Home Office, Prison Dept., 1990.

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Cookson, Hazel. Assessing the statistical significance of rare events. Home Office, Prison Department, 1990.

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E, Morrison Denton, and Henkel Ramon E. 1931-, eds. The significance test controversy: A reader. AldineTransaction, 2006.

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Salsburg, David. The use of restricted significance tests in clinical trials. Springer-Verlag, 1992.

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Wyss, Max, Kunihiko Shimazaki, and Akihiko Ito, eds. Seismicity Patterns, their Statistical Significance and Physical Meaning. Birkhäuser Basel, 1999. http://dx.doi.org/10.1007/978-3-0348-8677-2.

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1939-, Wyss Max, Shimazaki K. 1946-, and Ito Akihiko, eds. Seismicity patterns, their statistical significance and physical meaning. Birkhäuser Verlag, 1999.

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McDermott, C. John. Cointegration: Origins and significance for economists. Reserve Bank of New Zealand, Economic Dept., 1990.

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Hardy, David J. Does This Research Really Tell Me Anything? Understanding Statistical Significance. SAGE Publications Ltd, 2025. https://doi.org/10.4135/9781036222680.

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Book chapters on the topic "Statistical significance"

1

Franzen, Michael D. "Statistical Significance." In Encyclopedia of Clinical Neuropsychology. Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1251.

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Page, Matthew J. L. "Statistical Significance." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1251-3.

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Page, Matthew J. L. "Statistical Significance." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_1251.

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Turner, J. Rick. "Statistical Significance." In New Drug Development. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6418-2_9.

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Kubat, Miroslav. "Statistical Significance." In An Introduction to Machine Learning. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20010-1_12.

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Ziliak, Stephen. "Significance, Statistical." In Encyclopedia of Quality of Life and Well-Being Research. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_2869.

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Cicchetti, Domenic V. "Statistical Significance." In Encyclopedia of Autism Spectrum Disorders. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_1816.

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Newhart, Michelle, and Mildred L. Patten. "Statistical Significance." In Understanding Research Methods, 11th ed. Routledge, 2023. http://dx.doi.org/10.4324/9781003092049-75.

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Ziliak, Stephen. "Significance, Statistical." In Encyclopedia of Quality of Life and Well-Being Research. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-17299-1_2869.

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Hoem, Jan M. "Statistical Significance." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_84.

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Conference papers on the topic "Statistical significance"

1

Damani, Om P., and Shweta Ghonge. "Appropriately Incorporating Statistical Significance in PMI." In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2013. http://dx.doi.org/10.18653/v1/d13-1017.

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Abu-Shaira, Mohammad, and Weishi Shi. "Unveiling Statistical Significance of Online Regression Over Multiple Datasets." In 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2024. http://dx.doi.org/10.1109/mipr62202.2024.00051.

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Thompson, Brian, Nitika Mathur, Daniel Deutsch, and Huda Khayrallah. "Improving Statistical Significance in Human Evaluation of Automatic Metrics via Soft Pairwise Accuracy." In Proceedings of the Ninth Conference on Machine Translation. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.wmt-1.118.

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Peshev, Nedyalko, and Valentin Tsenev. "Significance of strain gauge test for evaluating the quality of LGA joints using statistical analysis." In 2024 International Conference on Information Technologies (InfoTech). IEEE, 2024. http://dx.doi.org/10.1109/infotech63258.2024.10701418.

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Biagiotti, Stephen F., Scott Riccardella, David Tomlinson, and Tony Rizk. "Metallurgical Methods Used to Assess the Significance of Pipeline Stress Cracking." In CORROSION 2016. NACE International, 2016. https://doi.org/10.5006/c2016-07139.

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Abstract Stress corrosion cracking (SCC) and Hydrogen Induced Cracking (HIC) continue to be significant challenges to the pipeline industry. The initial challenge is identifying “where” along a pipeline the damage may exist through inline inspection (ILI) or direct assessment (DA) methods. However, additional challenges must be overcome to realistically assess the significance of the damage to safe pipeline operation. These include characterizing the true extent of the SCC or HIC, estimating future crack behavior and predicting failure pressures. This paper presents the methods used to destruc

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Castro, Nuno, and Paulo J. Azevedo. "Time Series Motifs Statistical Significance." In Proceedings of the 2011 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2011. http://dx.doi.org/10.1137/1.9781611972818.59.

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Chinchor, Nancy. "Statistical significance of MUC-6 results." In the 6th conference. Association for Computational Linguistics, 1995. http://dx.doi.org/10.3115/1072399.1072404.

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Carterette, Ben. "Statistical Significance Testing in Information Retrieval." In ICTIR '15: ACM SIGIR International Conference on the Theory of Information Retrieval. ACM, 2015. http://dx.doi.org/10.1145/2808194.2809445.

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Carterette, Ben. "Statistical significance testing in information retrieval." In SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2014. http://dx.doi.org/10.1145/2600428.2602292.

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Urbano, Julián, Harlley Lima, and Alan Hanjalic. "Statistical Significance Testing in Information Retrieval." In SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2019. http://dx.doi.org/10.1145/3331184.3331259.

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Reports on the topic "Statistical significance"

1

Abadie, Alberto. Statistical Non-Significance in Empirical Economics. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w24403.

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Hoem, Jan M. The reporting of statistical significance in scientific journals. Max Planck Institute for Demographic Research, 2007. http://dx.doi.org/10.4054/mpidr-wp-2007-037.

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Martinez, Melissa. Hypothesis Testing. ConductScience, 2022. http://dx.doi.org/10.55157/cs20220615.

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Hypothesis testing is a statistical method used to evaluate the validity of a potential outcome within a defined significance level, comparing it with an alternative hypothesis. It involves establishing null and alternative hypotheses, making assumptions, calculating a test statistic, and selecting a significance level. The decision to accept or reject the null hypothesis is based on the observed test statistic. Terminologies include null and alternative hypotheses, critical region, critical value, errors, p-value, power of a test, and more. Hypothesis testing is crucial in statistical inferen

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Orbán, Levente. Lecture Short Notes: Introduction to Probability, Effect Size, and Hypothesis Testing. Orban Foundation, 2025. https://doi.org/10.69642/4593.

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This lecture introduces fundamental statistical concepts related to probability, effect size, and hypothesis testing. We explore the role of probability in inferential statistics, discuss the trade-offs between Type I and Type II errors, and demonstrate calculations using R programming. The importance of effect size in interpreting statistical significance is also highlighted. This document refines and expands upon the original lecture transcript to enhance coherence and depth.

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Luo, Minjing, Yilin Li, Yingqiao Wang, et al. The Fragility of Statistically Significant Findings from Depression Randomized Controlled Trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.4.0086.

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Review question / Objective: The Fragility of Statistically Significant Findings from Depression Randomized Controlled Trials. Condition being studied: Depression is a mental disorder characterized by a range of symptoms, including loss of memory and sleep, decreased energy, feelings of guilt or low mood, disturbed appetite, poor concentration, and an increased risk of suicide. According to a systematic analysis of the Global Burden of Disease Study 2019, depression is recognized as the leading cause of disease burden for mental disorders, accounting for the largest proportion of disability-ad

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Orbán, Levente. Lecture Notes: Null Hypothesis Testing and the t-test. Orban Foundation, 2025. https://doi.org/10.69642/5734.

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This document presents a structured overview of null hypothesis significance testing (NHST) and the t-test. Theoretical foundations, mathematical formulations, and base R implementations are provided to enhance understanding of statistical hypothesis testing in psychology.

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Sanchez-Jabba, Andres, Erick Villabon-Hinestroza, and Bernardo Romero-Torres. Inflation Expectations Measurement and its Effect on Inflation Dynamics in Colombia. Banco de la República, 2023. http://dx.doi.org/10.32468/be.1257.

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Accurate measurement of inflation expectations is crucial due to its significant impact on inflation dynamics and the potential for biased estimates when using different measurement methods. The main objective of this study is to determine whether the effect of inflation expectations on inflation dynamics in Colombia depends on the measurement method employed. We achieve this by estimating New-Keynesian Phillips Curves using various measurement methods for inflation expectations employing data from financial markets, economic surveys, and macroeconomic models. Our analysis focuses on any diffe

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Bonilla, Claudio A., and Christian A. Cancino. The Impact of the Seed Capital Program of SERCOTEC in Chile. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0011355.

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This paper seeks to measure the impact on small businesses in Chile of the Seed Capital Program implemented by Chile's Technical Cooperation Services (Servicio de Cooperación Técnica SERCOTEC). The results are mixed. On the one hand, the impact of sales is positive but its statistical significance depends on the model used. With regard to the number of employees, however, the results are positive and statistically significant regardless of the model used. The results also show that participating in the program has no incidence on the probability of later obtaining financing. This study highlig

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Zuloeta, José, and Roberto Machado. The Impact of the Business Cycle on Elasticities of Tax Revenue in Latin America. Inter-American Development Bank, 2012. http://dx.doi.org/10.18235/0011409.

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This paper estimates short-run and long-run elasticities of tax revenue with respect to GDP in eight Latin American countries using quarterly data. Taxes considered are corporate income tax (CIT), personal income tax (PIT), value-added tax (VAT), and overall taxes. Results indicate that long-run elasticities are statistically and economically larger than 1, whereas short-run elasticities appear not to be statistically different from zero in the majority of cases. Tax systems seem very elastic in Argentina, Colombia, Ecuador, Peru, and Venezuela. The CIT exhibits the largest estimated long-run

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Spielauer, Martin, and René Houle. Sample size and statistical significance of hazard regression parameters. An exploration by means of Monte Carlo simulation of four transition models based on Hungarian GGS data. Max Planck Institute for Demographic Research, 2004. http://dx.doi.org/10.4054/mpidr-wp-2004-020.

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