TY - JOUR
T1 - On statistical methods for comparison of intrasample morphometric variability
T2 - Zalavar revisited
AU - Moraga, Mauricio L.
AU - Rocco, Paola
AU - Miquel, Juan F.
AU - Nervi, Flavio
AU - Llop, Elena
AU - Chakraborty, Ranajit
AU - Rothhammer, Francisco
AU - Carvallo, Pilar
PY - 2000
Y1 - 2000
N2 - In studies of morphology, methods for comparing amounts of variability are often important. Three different ways of utilizing determinants of covariance matrices for testing for surplus variability in a hypothesis sample compared to a reference sample are presented: an F-test based on standardized generalized variances, a parametric bootstrap based on draws on Wishart matrices, and a nonparametric bootstrap. The F-test based on standardized generalized variances and the Wishart-based bootstrap are applicable when multivariate normality can be assumed. These methods can be applied with only summary data available. However, the nonparametric bootstrap can be applied with multivariate nonnormally distributed data as well as multivariate normally distributed data, and small sample sizes. Therefore, this method is preferable when raw data are available. Three craniometric samples are used to present the methods. A Hungarian Zalavar sample and an Austrian Berg sample are compared to a Norwegian Oslo sample, the latter employed as reference sample. In agreement with a previous study, it is shown that the Zalavar sample does not represent surplus variability, whereas the Berg sample does represent such a surplus variability. (C) 2000 Wiley-Liss, Inc.
AB - In studies of morphology, methods for comparing amounts of variability are often important. Three different ways of utilizing determinants of covariance matrices for testing for surplus variability in a hypothesis sample compared to a reference sample are presented: an F-test based on standardized generalized variances, a parametric bootstrap based on draws on Wishart matrices, and a nonparametric bootstrap. The F-test based on standardized generalized variances and the Wishart-based bootstrap are applicable when multivariate normality can be assumed. These methods can be applied with only summary data available. However, the nonparametric bootstrap can be applied with multivariate nonnormally distributed data as well as multivariate normally distributed data, and small sample sizes. Therefore, this method is preferable when raw data are available. Three craniometric samples are used to present the methods. A Hungarian Zalavar sample and an Austrian Berg sample are compared to a Norwegian Oslo sample, the latter employed as reference sample. In agreement with a previous study, it is shown that the Zalavar sample does not represent surplus variability, whereas the Berg sample does represent such a surplus variability. (C) 2000 Wiley-Liss, Inc.
KW - Generalized variance
KW - Multivariate variability
KW - Parametric and nonparametric bootstrap
KW - Zalavar
UR - http://www.scopus.com/inward/record.url?scp=0033847180&partnerID=8YFLogxK
U2 - 10.1002/1096-8644(200009)113:1<79::AID-AJPA7>3.0.CO;2-3
DO - 10.1002/1096-8644(200009)113:1<79::AID-AJPA7>3.0.CO;2-3
M3 - Article
C2 - 10954621
AN - SCOPUS:0033847180
SN - 0002-9483
VL - 113
SP - 79
EP - 84
JO - American Journal of Physical Anthropology
JF - American Journal of Physical Anthropology
IS - 1
ER -