Academic productivity and gender at Unesp
Keywords:
H index, text mining, equity, effect sizeAbstract
A spatial point process is understood as a set of points (events) irregularly distributed in space, generated by a stochastic probabilistic mechanism. Associating an attribute (mark) with the coordinate determines a marked point process. In the analysis of marked point processes, the interest lies in characterizing the pattern of interaction between the stochastic processes that generated the points and the marks. Analyses start with the characterization of first-order effects for a complete visualization of occurrence intensities. Assuming stationarity, a second-order analysis can be performed to characterize the spatial dependence present in the phenomenon. The data consist of georeferenced locations of occurrence of tree individuals in a native forest fragment and their respective diameters at breast height (DBH). This work aims to characterize the marked point processes by continuous variables, given by the DBH of native trees, through the estimation of the marked correlation function. All analyses were performed using the R software, developed by the R Core Team (2023). From the results, it was possible to observe the potential of the methods used to characterize the patterns and dynamics of the forest under study.
References
AGRESTI, A. Generalized odds ratios for ordinal data. Biometrics, JSTOR, p. 59–67, 1980.
ANUARIO Estatístico. Universidade Estadual Paulista Júlio de Mesquita Filho 2022. São Paulo, 2022. v. 1(2001). Disponível em: ⟨https://ape.unesp.br/anuario/flip/⟩. Acesso em: 7 de janeiro de 2024.
BARTOLUCCI, A. A.; TENDERA, M.; HOWARD, G. Meta-analysis of multiple primary pre vention trials of cardiovascular events using aspirin. The American journal of cardiology, Elsevier, v. 107, n. 12, p. 1796–1801, 2011.
BORNMANN, L.; DANIEL, H.-D. What do we know about the h index? Journal of the Ame rican Society for Information Science and technology, Wiley Online Library, v. 58, n. 9, p.1381–1385, 2007.
BOVA, A. Nonparametric Methods for Two Independent Samples in R: A Set of Useful Functions (Tutorial). 2022. Disponível em: ⟨https://rpubs.com/abova/nptest⟩.
BRUNNER, E.; BATHKE, A. C.; KONIETSCHKE, F. Rank and pseudo-rank procedures for independent observations in factorial designs: Using R and SAS. [S.l.]: Springer, 2018.
COHEN, J. Things i have learned (so far). American Psychologist, American Psycho logical Association, Washington, v. 45, n. 12, p. 1304–1312, 1990. Disponível em: ⟨https://doi.org/10.1037/0003-066X.45.12.1304⟩. Acesso em: 7 de janeiro de 2024.
COHEN, J. Things i have learned (so far). In: KAZDIN, A. E. (Ed.). Methodological issues and strategies in clinical research. Washington: American Psychological Association, 1992. p.315–333. 765 pp. Disponível em: ⟨https://doi.org/10.1037/10109-028⟩.
COHEN, J. The earth is round (p < .05). American psychologist, American Psychological As sociation, v. 49, n. 12, p. 997, 1994.
COHEN, J. Statistical power analysis for the behavioral sciences. [S.l.]: Academic press, 2013.
COSCRATO, V.; IZBICKI, R.; STERN, R. B. Agnostic tests can control the type I and type II errors simultaneously. Brazilian Journal of Probability and Statistics, Brazilian Statistical Association, v. 34, n. 2, p. 230–250, 2020.
FREEMAN, L. C. Elementary applied statistics: for students in behavioral science. (No Title),
FUNDER, D. C.; OZER, D. J. Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science, Sage Publications Sage CA: Los Angeles, CA, v. 2, n. 2, p. 156–168, 2019.
GELMAN, A. Statistical Modeling, Causal Inference, and Social Science. 2009. ⟨https://statmodeling.stat.columbia.edu/2009/06/18/the sample size/⟩. Acesso em: 7 de janeiro de 2024.
GIGNAC, G. E.; SZODORAI, E. T. Effect size guidelines for individual differences researchers. Personality and individual differences, Elsevier, v. 102, p. 74–78, 2016.
GRISSOM, R. J.; KIM, J. J. Effect sizes for research: A broad practical approach. [S.l.]: La wrence Erlbaum Associates Publishers, 2005.
HIRSCH, J. E. An index to quantify an individual’s scientific research output. Proceedings of the National academy of Sciences, National Acad Sciences, v. 102, n. 46, p. 16569–16572, 2005.
KENDALL, M. G. A new measure of rank correlation. Biometrika, JSTOR, v. 30, n. 1/2, p. 81–93, 1938.
KING, B. M.; ROSOPA, P. J.; MINIUM, E. W. Statistical reasoning in the behavioral sciences. [S.l.]: John Wiley & Sons, 2018.
LOVAKOV, A.; AGADULLINA, E. R. Empirically derived guidelines for effect size interpreta tion in social psychology. European Journal of Social Psychology, Wiley Online Library, v. 51, n. 3, p. 485–504, 2021.
MCGRAW, K. O.; WONG, S. P. A common language effect size statistic. Psychological bulletin, American Psychological Association, v. 111, n. 2, p. 361, 1992.
NOETHER, G. E. Sample size determination for some common nonparametric tests. Journal of the American Statistical Association, Taylor & Francis, v. 82, n. 398, p. 645–647, 1987.
NOMES no Brasil. 2010. ⟨https://censo2010.ibge.gov.br/nomes/#/search⟩. Acesso em: 06 abr 2022.
R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria, 2018. Disponível em: ⟨https://www.R-project.org/⟩.
SANTO, H. E.; DANIEL, F. Calcular e apresentar tamanhos do efeito em trabalhos científicos (1): as limitações do p< 0,05 na análise de diferenças de médias de dois grupos (calculating and reporting effect sizes on scientific papers (1): P< 0.05 limitations in the analysis of mean differences of two groups). Revista Portuguesa de Investigaçãao Comportamental e Social, v. 1, n. 1, p. 3–16, 2017.
SAWILOWSKY, S. S. New effect size rules of thumb. Journal of modern applied statistical methods, v. 8, n. 2, p. 26, 2009.
SCOPUS. 2023. ⟨https://www.scopus.com/search/form.uri?display=basic#basic⟩. Acesso em: 03 ago 2022.
TOMCZAK, M.; TOMCZAK, E. The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Akademia Wychowania Fizycznego w Poznaniu, 2014.
TUKEY, J. W. et al. Exploratory data analysis. Reading, MA: Addison-Wesley, 1977. v. 2.
VARGHA, A.; DELANEY, H. D. A critique and improvement of the cl common language effect size statistics of mcgraw and wong. Journal of Educational and Behavioral Statistics, Sage Publications Sage CA: Los Angeles, CA, v. 25, n. 2, p. 101–132, 2000.
Downloads
Published
How to Cite
Issue
Section
License
Proposta de Política para Periódicos de Acesso Livre
Autores que publicam nesta revista concordam com os seguintes termos:
- Autores mantém os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a Licença Creative Commons Attribution que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
- Autores têm autorização para assumir contratos adicionais separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
- Autores têm permissão e são estimulados a publicar e distribuir seu trabalho online (ex.: em repositórios institucionais ou na sua página pessoal) a qualquer ponto antes ou durante o processo editorial, já que isso pode gerar alterações produtivas, bem como aumentar o impacto e a citação do trabalho publicado (Veja O Efeito do Acesso Livre).