Multifactorial analysis

Theunissen, K. Verfaillie, C.M. (2005) A multifactorial analysis of umbilical cord blood, adult bone marrow and mobilized peripheral blood progenitors using the improved ML IC assay. Experimental Hematology, 33,165-172. 

Kita T, Yokoyama K, Higuchi T, Kinuya S, Taki J, Nakajima K, Michigishi T, Tonami N. Multifactorial analysis on the short-term side effects occurring within 96 hours after radioiodine-131 therapy for differentiated thyroid carcinoma. Ann Nucl Med 2004 18(4) 345-9. 

Uter, W., Pfahlberg, A., Gefeller, O., Geier, J., and Schnuch, A., Risk factors for contact allergy to nickel — results of a multifactorial analysis, Contact Dermatitis, 48, 33, 2003. 

The well-documented existence of carcinogenic and anticarcinogenic agents strongly suggests that a time assessment of carcinogenic risk for a particular PAH can be evaluated only through a multifactorial analysis. One of... 

Metabolism New-onset diabetes mellitus is more common in hypertensive patients with abdominal obesity after short-term exposure to hydrochlorothiazide. Administration of hydrochlorothiazide 25 mg/day to 395 patients led to a 7-8% mean increase in fasting blood glucose and also more diagnoses of new-onset diabetes mellitus (13/ 195 versus 4/200) [9 ]. In a complex post hoc multifactorial analysis the problem was shown to occur particularly in those with abdominal obesity at baseline. 

As already indicated, modern mathematical methods for multifactorial analysis of risk further enhance our ability to quantitate coronary-proneness to development of coronary heart disease (3,21). 

Palmer LJ, Cookson WOCM. Atopy and asthma. In Genetic Analysis of Multifactorial Diseases (Sham PC, Bishop T,... 

A final source of variation in microarray experiments is derived from measurement errors. Measurement errors may occur during the processes of image acquisition and normalization or during the multifactorial data analysis required to extract biological relevance from the collected data. The effect of measurement error can be minimized by ensuring consistency in all aspects of microarray experimentation. If possible, experiments should be performed by the same technician, and subsequent data analyses be applied to all datasets consistently. 

The paper by Cochrane, St. Leger, and Moore (1978) typifies the issues associated with many early studies. Specifically, they relied on cross sections with multiple countries and often limited the analysis to simple correlations. Because determinants of life expectancy are multifactorial, national studies are more likely to detect differences than international studies. It is also critically important to include adequate control variables. In fact, a later study (Cremieux, Ouellette, and Meilleur 1999) based on extensive national data suggests that a 10% increase in health care spending reduces infant mortality by 0.5% for males and 0.4% for females while increasing life expectancy by half a year for males and three months for females. The current study uses similar modeling and data hence, results on the effect of pharmaceuticals reported below can be put in perspective relative to the overall effect of health care spending from that earlier research. 

Multisensor devices may be based on an array of sensing units that present different sensitivities for each component of a collection of substrates to be determined [8.238], resulting in a specific signature for each compound. With a sufficient number of signals the composite response may be deconvoluted and the nature and concentrations of the substances determined using techniques such as multifactorial system analysis aided by neural network procedures. 

For the purpose of the analysis the interfering water components have to be determined and the concentration levels for the multifactorial plan have to be defined. 

Cordingley HC, Roberts SL, Tooke P, Armitage JR, Lane PW, Wu W, Wildsmith SE. Multifactorial screening design and analysis of SELDI-TOF ProteinChip array optimization experiments. Biotechniques 2003 34 364-365, 368-373. 

The simplest experiments are those in which one treatment (factor) is applied at a time to the samples. This approach is likely to give clear-cut answers, but it could be criticized for lacking realism. In particular, it cannot take account of interactions among two or more conditions that are likely to occur in real life. A multifactorial experiment (Fig. 10.4) is an attempt to do this the interactions among treatments can be analysed by specialized forms of analysis of variance. 

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