Franceschi, P

Gasperi, F.

Giacalone, D

Menghi, L

English

Archivio istituzionale della ricerca - Fondazione Edmund Mach

P2.140	 A	bootstrap-based	approach	for	sample	size	calculation	whentraditional	estimations	are	not	possibleLeonardo	Menghi1,2,3,	Pietro	Franceschi3,	Davide	Giacalone2,	Flavia	Gasperi1,31University	of	Trento	Center	Agriculture	Food	Environment,	Trento,	Italy.	2University	of	Southern	Denmark,Department	of	Technology	and	Innovation,	Odense,	Denmark.	3Edmund	Mach	Foundation	Research	andInnovation	Centre,	San	Michele	All	Adige,	ItalyAbstractIn	sensory	science,	formal	sample	size	estimations	are	seldom	used,	especially	when	the	magnitude	of	theunderlying	phenomena	are	hard	to	estimate.	This	may	lead	to	underpowered	studies	and	lower	thereproducibility	of	sensory	studies.		In	the	impossibility	of	using	traditional	techniques,	a	simulation-basedapproach	based	on	sampling	from	existing	data	may	be	a	viable	solution.	We	demonstrate	this	approach	with	a	case	study	focusing	on	the	possible	relation	between	oral	and	gutmicrobiota	and	sensory	perception.	Here,	we	employed	a	bootstrap	with	replacement	approach	to	estimate	theminimum	sample	size	needed	to	replicate	the	intra-sample	gut	microbial	diversity	(Shannon	α-diversity)	andsensory	responsiveness	(PROP	status)	from	two	reference	cohorts,	previously	assessed	for	gut	microbialcomposition	(American	Gut	project;	AG;	N=474)	and	inter-individual	variability	on	sensory	perception	(ItalianTaste	project;	IT;	N=605).	Firstly,	we	randomly	sampled	an	increasingly	higher	number	of	participants	(from	N=5	to	N=AG;	10k	timeseach)	to	observe	the	minimum	sample	size	showing	the	same	median	(Mann-Whitney	test;	p>0.05)	and	amaximum	reduction	<20%	in	the	IQR	of	the	AG	cohort	α-diversity	(p<0.05).	Then,	we	estimated	the	proportionof	Non-,	Medium-,	and	Super-Tasters	from	the	IT	dataset	and	repeated	the	analysis	to	obtain	the	minimumsample	size	reproducing	the	same	PROP	status	distribution	(chi-square	statistic;	p>0.05)	of	the	IT	cohort.	Wefound	that	N=106	was	the	minimum	sample	size	needed	to	replicate	the	overall	microbial	diversity	and	thePROP	status	distribution	of	both	cohorts.	Reference	data	were	then	compared	to	actual	data,	which	confirmedthe	similarity	of	cohorts.	Overall,	a	bootstrap-based	approach	appears	to	be	a	suitable	method	to	correctly	calculate	sample	size	whentraditional	estimations	are	not	possible.	In	the	attempt	to	further	encourage	formal	sample	size	calculations	insensory	studies,	our	approach	is	useful	especially	in	exploratory	studies	based	on	newly	hypothesizedinferences.		KeywordsSample	size	calculationsBootstrapping

A bootstrap-based approach for sample size calculation when traditional estimations are not possible

https://openpub.fmach.it/bitstream/10449/77678/3/2022%20P2.140%20Menghi.pdf

A bootstrap-based approach for sample size calculation when traditional estimations are not possible

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