The one-factor-at-a-time method,[1] also known as one-variable-at-a-time, OFAT, OF@T, OFaaT, OVAT, OV@T, OVaaT, or monothetic analysis is a method of designing experiments involving the testing of factors, or causes, one at a time instead of multiple factors simultaneously.
OFAT is favored by non-experts, especially in situations where the data is cheap and abundant.
There exist cases where the mental effort required to conduct a complex multi-factor analysis exceeds the effort required to acquire extra data, in which case OFAT might make sense. Furthermore, some researchers have shown that OFAT can be more effective than fractional factorials under certain conditions (number of runs is limited, primary goal is to attain improvements in the system, and experimental error is not large compared to factor effects, which must be additive and independent of each other).[2][3]
Disadvantagesedit
In contrast, in situations where data is precious and must be analyzed with care, it is almost always better to change multiple factors at once. A middle-school-level example illustrating this point is the family of balance puzzles, which includes the Twelve Coins puzzle. At the undergraduate level, one could compare Bevington's[4]GRIDLS versus GRADLS. The latter is far from optimal, but the former, which changes only one variable at a time, is worse. See also the factorial experimental design methods pioneered by Sir Ronald A. Fisher. Reasons for disfavoring OFAT include:
OFAT requires more runs for the same precision in effect estimation
OFAT cannot estimate interactions
OFAT can miss optimal settings of factors.
Designed experiments remain nearly always preferred to OFAT with many types and methods available, in addition to fractional factorials which, though usually requiring more runs than OFAT, do address the three concerns above.[5] One modern design over which OFAT has no advantage in number of runs is the Plackett-Burman which, by having all factors vary simultaneously (an important quality in experimental designs),[5] gives generally greater precision in effect estimation.
^Razavi, Saman; Gupta, Hoshin V. (2015). "What do we mean by sensitivity analysis? The need for comprehensive characterization of "global" sensitivity in Earth and Environmental systems models". Water Resources Research. 51 (5): 3070–3092. Bibcode:2015WRR....51.3070R. doi:10.1002/2014wr016527. ISSN 0043-1397.
^Friedman, M., and Savage, L. J. (1947), “Planning Experiments Seeking Maxima,” in Techniques of Statistical Analysis, eds. C. Eisenhart, M. W. Hastay, and W. A. Wallis, New York: McGraw-Hill, pp. 365-372.
^Daniel, C. (1973),“One-at-a-Time Plans,” Journal of the American Statistical Association 68, 353-360
^Bevington and Robinson, Data Reduction and Error Analysis for the Physical Sciences, 2nd Ed. McGraw–Hill (1992)
^ abCzitrom, Veronica (1999). "One-Factor-at-a-Time Versus Designed Experiments". American Statistician. 53 (2): 126–131. doi:10.2307/2685731. JSTOR 2685731.
January 01, 1970
factor, time, method, factor, time, method, also, known, variable, time, ofat, ofaat, ovat, ovaat, monothetic, analysis, method, designing, experiments, involving, testing, factors, causes, time, instead, multiple, factors, simultaneously, contents, advantages. The one factor at a time method 1 also known as one variable at a time OFAT OF T OFaaT OVAT OV T OVaaT or monothetic analysis is a method of designing experiments involving the testing of factors or causes one at a time instead of multiple factors simultaneously Contents 1 Advantages 2 Disadvantages 3 See also 4 ReferencesAdvantages editOFAT is favored by non experts especially in situations where the data is cheap and abundant There exist cases where the mental effort required to conduct a complex multi factor analysis exceeds the effort required to acquire extra data in which case OFAT might make sense Furthermore some researchers have shown that OFAT can be more effective than fractional factorials under certain conditions number of runs is limited primary goal is to attain improvements in the system and experimental error is not large compared to factor effects which must be additive and independent of each other 2 3 Disadvantages editIn contrast in situations where data is precious and must be analyzed with care it is almost always better to change multiple factors at once A middle school level example illustrating this point is the family of balance puzzles which includes the Twelve Coins puzzle At the undergraduate level one could compare Bevington s 4 GRIDLS versus GRADLS The latter is far from optimal but the former which changes only one variable at a time is worse See also the factorial experimental design methods pioneered by Sir Ronald A Fisher Reasons for disfavoring OFAT include OFAT requires more runs for the same precision in effect estimation OFAT cannot estimate interactions OFAT can miss optimal settings of factors Designed experiments remain nearly always preferred to OFAT with many types and methods available in addition to fractional factorials which though usually requiring more runs than OFAT do address the three concerns above 5 One modern design over which OFAT has no advantage in number of runs is the Plackett Burman which by having all factors vary simultaneously an important quality in experimental designs 5 gives generally greater precision in effect estimation See also editCeteris paribusReferences edit Razavi Saman Gupta Hoshin V 2015 What do we mean by sensitivity analysis The need for comprehensive characterization of global sensitivity in Earth and Environmental systems models Water Resources Research 51 5 3070 3092 Bibcode 2015WRR 51 3070R doi 10 1002 2014wr016527 ISSN 0043 1397 Friedman M and Savage L J 1947 Planning Experiments Seeking Maxima in Techniques of Statistical Analysis eds C Eisenhart M W Hastay and W A Wallis New York McGraw Hill pp 365 372 Daniel C 1973 One at a Time Plans Journal of the American Statistical Association 68 353 360 Bevington and Robinson Data Reduction and Error Analysis for the Physical Sciences 2nd Ed McGraw Hill 1992 a b Czitrom Veronica 1999 One Factor at a Time Versus Designed Experiments American Statistician 53 2 126 131 doi 10 2307 2685731 JSTOR 2685731 Retrieved from https en wikipedia org w index php title One factor at a time method amp oldid 1166766862, wikipedia, wiki, book, books, library,
