La estimación del error en métodos cuantitativos para identificación humana: un experimento con las arcadas dentales
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Los efectos del error de medición (EM) intra e inter observador en los datos empleados en métodos cuantitativos en la identificación humana, deben ser evaluados para evitar la aparición de errores estadísticos en la interpretación de datos, y la consecuente generación de falsos positivos o negativos. El objetivo fue evaluar el error intra e inter en nueve observadores en un protocolo de 20 landmarks, caracterizando su fluctuación en cuatro iteraciones independientes. Se contrastó la hipótesis de que el patrón del error de medición disminuye en función del tiempo y en relación con la formación y/o área académica del observador (experiencia). Para ello, se fenotiparon 139 fotografías de alta resolución de modelos dentales de 45 individuos de la Colección Odontológica Nacional de Ciencia Forense de la UNAM. Después, mediante el uso la morfometría geométrica y estadística multivariada se analizó la variación general de la muestra con un diseño experimental anidado por observadores e iteraciones. Los resultados fueron contrarios a lo esperado, los datos no muestran una disminución del error en función del tiempo. También, que el error inter fue mayor que el intraobservador, como otros estudios han reportado. La mayor frecuencia de error fue entre observadores por la secuencia de posicionamiento de landmarks. Con base en los resultados se recomiendan generalidades para evitar la aparición de error en estudios morfogeométricos, la principal es la inclusión de reportes de error intra e inter observador en los peritajes que usen mediciones o digitalizaciones.
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Algee-Hewitt BFB, Wheat AD. 2016. The reality of virtual anthropology: Comparing digitizer and laser scan data collection methods for the quantitative assessment of the cranium. Am J Phys Anthropol 160:148–155.
Arnqvist G, Martensson T. 1998. Measurement error in geometric morphometrics: empirical strategies to asses and reduce its impact on measures of shape. Acta Zool Acad Sci Hungaricae 44:73–96.
Bennett KA, Osborne RH. 1986. Interobserver measurement reliability in anthropometry. Hum Biol 58:751–759.
Bookstein FL. 1991. Morphometric tools for landmark data. Cambridge, Massachusetts,USA: Cambridge University Press.
Byrnes JF, Kenyhercz MW, Berg GE. 2017. Examining Interobserver Reliability of Metric and Morphoscopic Characteristics of the Mandible. J Forensic Sci 62:981–985.
Corner B, Lele S, Richtsmeier R. 1992. Measuring precision of three-dimensional landmark data. J Quant Anthr 3:347–59.
Von Cramon-Taubadel N, Frazier BC, Lahr MM. 2007. The problem of assessing landmark error in geometric morphometrics: Theory, methods, and modifications. Am J Phys Anthropol 134:24–35.
Filzmoser P. 2005. Identification of Multivariate Outliers: A Performance Study. Austrian J Stat 34:127–138–127–138.
Filzmoser P, Gregorich M. 2020. Multivariate Outlier Detection in Applied Data Analysis: Global, Local, Compositional and Cellwise Outliers. Math Geosci 2020 528 52:1049–1066.
Fourie Z, Damstra J, Gerrits PO, Ren Y. 2011. Evaluation of anthropometric accuracy and reliability using different three-dimensional scanning systems. Forensic Sci Int 207:127–134.
Gaito J, Gifford EC. 1958. Components of Variance in Anthropometry. Hum Biol 30:120.
Goodall C. 1991. Procrustes Methods in the Statistical Analysis of Shape. Source J R Stat Soc Ser B 53.
Gordon CC, Bradtmiller B. 1992. Interobserver error in a large scale anthropometric survey. Am J Hum Biol 4:253–263.
Greene DL. 1984. Fluctuating dental asymmetry and measurement error. Am J Phys Anthropol 65:283–9.
Guyatt G, Cook D, Haynes B. 2004. Evidence based medicine has come a long way. Br Med J 329:990–991.
Guyatt GH. 1991. Evidence-based medicine. ACP J Club 114.
IUPAC. 1997. Compendium of chemical terminology. Oxford, UK: Blackwell Scientific.
Jamison PL, Zegura SL. 1974. A univariate and multivariate examination of measurement error in anthropometry. Am J Phys Anthropol 40:197–203.
Jasso-Cuéllar J, Gil-Chavarría I, Quinto-Sánchez M. 2020. Anterior dental arch shape and human identification: Kieser et al. method applied to 2D-3D dental models in Mexican population. Forensic Sci Int Reports 2:100161.
Kemper HCG, Pieters JJL. 1974. Comparative study of anthropometric measurements of the same subjects in two different institutes. Am J Phys Anthropol 40:341–343.
Kieser JA, Bernal V, Neil Waddell J, Raju S. 2007. The Uniqueness of the Human Anterior Dentition: A Geometric Morphometric Analysis. J Forensic Sci 52:671–677.
Klingenberg CP. 2011. MorphoJ: an integrated software package for geometric morphometrics. Mol Ecol Resour 11:353–357.
Kouchi M, Mochimaru M, Tsuzuki K, Yokoi T. 1999. Interobserver errors in anthropometry. J Hum Ergol (Tokyo) 28:15–24.
Llamosa L, Contreras L, Arbelaez M. 2007. Estudio de repetibilidad y reproducibilidad utilizando el método de promedios y rangos para el aseguramiento de la calidad de los resultados de calibración de acuerdo con la norma técnica NTC-ISO/IEC 17025. Sci Tech XIII:455–460.
MacLeod N. 2002. Geometric morphometrics and geological shape-classification systems. Earth-Sci Rev 59:27–47.
Menéndez LP. 2017. Comparing Methods to Assess Intraobserver Measurement Error of 3D Craniofacial Landmarks Using Geometric Morphometrics Through a Digitizer Arm. J Forensic Sci 62:741–746.
Merilä J, Björklund M. 1995. Fluctuating Asymmetry and Measurement Error. Syst Biol 44:97–101.
Molto JE. 1979. The assessment and meaning of intraobserver error in population studies based on discontinuous cranial traits. Am J Phys Anthropol 51:333–344.
Muñoz-Muñoz F, Perpiñán D. 2010. Measurement Error in Morphometric Studies: Comparison between Manual and Computerized Methods. Ann Zool Fennici 47:46–56.
Muñoz-Muñoz F, Sans-Fuentes MA, López-Fuster MJ, Ventura J. 2011. Evolutionary modularity of the mouse mandible: dissecting the effect of chromosomal reorganizations and isolation by distance in a Robertsonian system of Mus musculus domesticus. J Evol Biol 24:1763–1776.
NAS. 2009. Strengthening Forensic Science in the United States: A Path Forward.
Neale W, Hessel D, Terpstra T. 2011. Photogrammetric measurement error associated with lens distortion. SAE Tech Pap 01–0286:1–54.
Ossenberg N. 1979. Within and between race distance in population studies based on discrete traits of the human skull. Am J Phys Anthr 45:701–716.
Pérez-Pérez A, Alesan A, Roca L. 1990. Measurement error: Inter-and Intraobserver Variability. An Empiric Study. Int J Anthropol 5:129–135.
Pérez S, González P, Bernal V, Del Papa M, Barreiro A, Negro C, Martínez L. 2004. El error de observación y su influencia en los análisis morfológicos de restos óseos humanos: Datos de variación continua. Rev Argentina Antropol Biológica 6:61–75.
Perez SI, Gonzalez PN, Bernal V, Del Papa M, Barreiro A, Negro C, Martínez L. 2004. El error de observación y su influencia en los Análisis morfológicos de restos óseos humanos. Datos de variación continua. Rev Argentina Antropol Biológica 6:61–75.
Rabinovich S. 1994. Measurement Errors: theory and practice. New York: Amer Inst of Physics.
Renner MAM, Brown EA, Wardle GM, Renner MAM, Brown EA, Wardle GM. 2013. Averaging v. outlier removal. Decrypting variance among cryptic Lejeunea species (Lejeuneaceae: Jungermanniopsida) using geometric morphometrics. Aust Syst Bot 26:13–30.
Richtsmeier JT, Paik CH, Elfert PC, Cole TM, Dahlman HR. 1995. Precision, repeatability, and validation of the localization of cranial landmarks using computed tomography scans. Cleft Palate Craniofac J 32:217–27.
Robinson C, Terhune CE. 2017. Error in geometric morphometric data collection: Combining data from multiple sources. Am J Phys Anthropol 164:62–75.
Rohlf FJ. 2003. Bias and error in estimates of mean shape in geometric morphometrics. J Hum Evol 44:665–83.
Rohlf FJ. 2015. The tps series of software. Hystrix 26:1–4.
Rohlf FJ, Slice DE. 1990. Extensions of the Procrustes method for the optimal superimposition of landmarks. Syst Zool 39:40–59.
Ross AH, Williams S. 2008. Testing repeatability and error of coordinate landmark data acquired from crania. J Forensic Sci 53:782–5.
Sackett DL. 1997. Evidence-based medicine. Semin Perinatol 21:3–5.
Sackett DL, Rosenberg WMC, Gray JAM, Haynes RB, Richardson WS. 1996. Evidence based medicine: what it is and what it isn’t. BMJ 312.
Shearer BM, Cooke SB, Halenar LB, Reber SL, Plummer JE, Delson E, Tallman M. 2017. Evaluating causes of error in landmark-based data collection using scanners. PLoS One 12:e0187452.
Sheets H., Bush PJ, Bush MA. 2013. Patterns of Variation and Match Rates of the Anterior Biting Dentition: Characteristics of a Database of 3D-Scanned Dentitions. J Forensic Sci 58:60–68.
Sholts SB, Flores L, Walker PL, Wärmländer SKTS. 2011. Comparison of coordinate measurement precision of different landmark types on human crania using a 3D laser scanner and a 3D digitiser: Implications for applications of digital morphometrics. Int J Osteoarchaeol 21:535–543.
Sholts SB, Wärmländer SKTS, Flores LM, Miller KWP, Walker PL. 2010. Variation in the measurement of cranial volume and surface area using 3d laser scanning technology. J Forensic Sci 55:871–876.
Singleton M. 2002. Patterns of cranial shape variation in the Papionini (Primates: Cercopithecinae). J Hum Evol 42(5), 547.
Sokal RR, Rohlf FJ. 1995. Biometry: the principles and practice of statistics in biological research. San Francisco: W. H. Freeman.
Taylor B, Kuyatt C. 2009. Guidelines for evaluating and expressing the uncertainty of NIST measurement results. NIST Technical Note 1297-DIANE Publishing.
Utermohle CJ, Zegura SL. 1982. Intra- and interobserver error in craniometry: A cautionary tale. Am J Phys Anthropol 57:303–310.
Utermohle CJ, Zegura SL, Heathcote GM. 1983. Multiple observers, humidity, and choice of precision statistics: Factors influencing craniometric data quality. Am J Phys Anthropol 61:85–95.
Viscosi V, Fortini P, Slice DE, Loy A, Blasi C. 2009. Geometric morphometric analyses of leaf variation in four oak species of the subgenus Quercus (Fagaceae). http://dx.doi.org/101080/11263500902775277 143:575–587.
Wolak ME, Fairbairn DJ, Paulsen YR. 2012. Guidelines for estimating repeatability. Methods Ecol Evol 3:129–137.
Yezerinac SM, Lougheed SC, Handford P. 1992. Measurement Error and Morphometric Studies: Statistical Power and Observer Experience. Syst Biol 41:471–482.
Zelditch M, Swiderski D, Sheets H, Fink W. 2004. Geometric morphometric for biologists: a primer. London: Academic Press.
Zimek A, Filzmoser P. 2018. There and back again: Outlier detection between statistical reasoning and data mining algorithms. Wiley Interdiscip Rev Data Min Knowl Discov 8:e1280.