Sample-Size Planning for Multivariate Data: A Raman-Spectroscopy-Based Example

2018 ◽  
Vol 90 (21) ◽  
pp. 12485-12492 ◽  
Author(s):  
Nairveen Ali ◽  
Sophie Girnus ◽  
Petra Rösch ◽  
Jürgen Popp ◽  
Thomas Bocklitz
Keyword(s):  
Raman Spectroscopy ◽  
Sample Size ◽  
Multivariate Data ◽  
Sample Size Planning

scholarly journals Erratum to: Power Analysis and Sample Size Planning in Ancova Designs

Psychometrika ◽  
2021 ◽  
Author(s):  
Gwowen Shieh
Keyword(s):  
Sample Size ◽  
Power Analysis ◽  
Sample Size Planning

A Correction to this paper has been published: https://doi.org/10.1007/s11336-019-09692-3

Assessing sample size and variable number in multivariate data, with specific reference to cone morphology variation in a population of Picea sitchensis

1985 ◽  
Vol 63 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Rob Scagel ◽  
Y. A. El-Kassaby ◽  
J. Emanuel
Keyword(s):  
Sample Size ◽  
Multivariate Data ◽  
Variable Number ◽  
Picea Sitchensis ◽  
Interindividual Variation ◽  
Specific Reference ◽  
Size Estimation ◽  
Pilot Studies ◽  
Nested Models ◽  
Cone Morphology

A multivariate extension of univariate sample size estimation is outlined that enables one to determine sample size for a multivariate study. The procedure is presented and illustrated by application to intraindividual and interindividual variation of cone morphology in a population of Picea sitchensis (Bong.) Carr. The method involves the stabilization of a scalar estimate of the structure of the correlation matrix (the determinant) among variables for a given sample size. The sample-specific dependency of previously described methods is avoided by random selection of several replicates in nonstructured and structured (nested) models. The procedure is best applied in pilot studies where it can aid in the characterization of multivariate data prior to analysis. Additionally, repeatability estimates for cone scale morphology are presented.

Classification of iron-based inks by means of micro-Raman spectroscopy and multivariate data analysis

2013 ◽  
Vol 44 (9) ◽  
pp. 1299-1305 ◽  
Author(s):  
Giovanna Piantanida ◽  
Eva Menart ◽  
Marina Bicchieri ◽  
Matija Strlič
Keyword(s):  
Raman Spectroscopy ◽  
Data Analysis ◽  
Multivariate Data Analysis ◽  
Multivariate Data ◽  
Micro Raman Spectroscopy ◽  
Iron Based
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