.png){kind=icon}
Return
Experimental design and multiple response optimization. Using the desirability function in analytical methods development
.png){kind=icon}
PRE
AI
DOI：10.1016/j.talanta.2014.01.034.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. (C) 2014 Elsevier BM. All rights reserved.
Keywords:
Experimental design
Response transformation
Multiple response optimization
Desirability function
Journal
IF:
6.1
Papers:
2.6W
Citations:
6.3W
Organization
Cited Papers
ShareSaveThe use of experimental design in the development of an HPLC-ECD method for the analysis of captopril.png)
TALANTA
TALANTAIF6.1
PREAI
ShareSaveShareSaveShareSave
ShareSaveA novel ion-pairing chromatographic method for the simultaneous determination of both nicarbazin components in feed additives: Chemometric tools for improving the optimization and validationTALANTA
OAAI
TALANTAIF6.1
OAAIShareSaveShareSave
View more