Table 7:

Variable selection and clustering results based on AgeWise data. For the skewvarsel-p algorithm, the specific permutation of data types is provided in parentheses, where P=PSG, A=Actigraphy, and D=Diary. Variables represent averages over multiple nights of observation unless prefixed with “sd”, in which case they represent the standard deviation. The P, A, or D in parentheses after each variable indicates the data source through which it was measured. See Table 1 for full variable descriptions and abbreviations.

Algorithm	Variables Selected	Skewness Rankings	Spearman r Median (Min., Max)	Cluster Distribution	Number of Clusters
clustvarsel	SL(P), sdSL(D), SL(D), SL(A), RL(P), RLA(P)	5,14,7,6,20	0.07(0.003,0.93)	CFUST	2
skewvarsel	%Delta(P), Delta(P), Bed(P)	30,28,60	0.05(0.02,0.99)	MSN	4
skewvarsel-p(PDA)	%Delta(P), sdMood(D), sdSE(A), Delta(P), TST(P)	30,43,4,28,56	0.16(0.002,0.99)	CFUST	4
skewvarsel-p(PAD)	%Delta(P), sdSL(A), sdSL(D), Delta(P), SL(D), TST(P)	30,9,14,28,6,56	0.15(0.07,0.83)	CFUST	3
skewvarsel-p(APD)	SL(A), %Delta(P), sdWASO(D), Delta(P)	6,30,21,28	0.13(0.03,0.99)	CFUST	2
skewvarsel-p(DAP)	sdSL(D), SL(A), SL(P), SL(D), NREM(P)	14,6,5,6,67	0.19(0.05,0.83)	CFUST	2
skewvarsel-p(DPA)	sdSL(D), SL(P), SL(A), SL(D), NREM(P)	14,6,5,6,67	0.19(0.05,0.83)	CFUST	2
skewvarsel-p(ADP)	SL(A), sdWASO(D), N2(P), sdSL(A)	6,21,70,9	0.20(0.03,0.92)	CFUST	2