Statistical analysis of the impact of spectral correlation on observed formation constants from UV–visible spectroscopic measurements

Meinrath, Ginther; Lis, Stefan; Piskula, Zbigniew
January 2004
Analytical & Bioanalytical Chemistry;Jan2004, Vol. 378 Issue 1, p221
Academic Journal
Information retrieved from UV–visible spectroscopic data by application of a self-modelling factor analysis algorithm showed apparently systematically shifted thermodynamic properties for the same chemical system as a function of spectral slit widths. This empirical observation triggered a systematic investigation into the likely effects of residual and spectral correlation on the numerical results from quantitative spectroscopic investigations. If slit width was a nuisance factor it would reduce the comparability of information evaluated from spectroscopic data. The influence of spectral slit width was investigated by simulation, i.e. by generating and evaluating synthetic spectra with known properties. The simulations showed that increasing spectral correlation may introduce bias into factor analysis evaluations. By evaluation of the complete measurement uncertainty budget using threshold bootstrap target factor (TB CAT) analysis, the apparent shifts are insignificant relative to the total width of the quantity’s measurement uncertainty. Increasing the slit widths causes some systematic effects, for example broadening of the registered spectral bands and reduction of spectral noise, because of higher light intensity passing to the detector. Hence, the observed systematic shifts in mean values might be caused by some latent correlation. As a general conclusion, slit width does not affect bias. However, the simulations show that spectral correlation and residual correlation may cause bias. Residual correlation can be taken into account by computer-intensive statistical methods, for example moving block or threshold bootstrap analysis. Spectral correlation is a property of the chemical system under study and cannot be manipulated. As a major result, evidence is given showing that stronger spectral correlation (r<-0.7) causes non-negligible bias in the evaluated thermodynamic information from such a system.


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