Temporal organization of rest defined by actigraphy data in healthy and childhood chronic fatigue syndrome children

Kawabata, Minako; Ueno, Taro; Tomita, Jun; Kawatani, Junko; Tomoda, Akemi; Kume, Shoen; Kume, Kazuhiko

doi:10.1186/1471-244X-13-281

Table 1 Statistical tests for the significance of the power-law property in distributions of rest bouts according to the method described by Clauset et al. (control)

From: Temporal organization of rest defined by actigraphy data in healthy and childhood chronic fatigue syndrome children

No.	Basic parameters				Power law vs. exponential						Power law test
	Basic parameters				24h		UP		DOWN		Power law test
	n	<x>	Total	sd	LR	p	LR	p	LR	p	xmax	xmin	α	ntail	p’
1	570	12.3	6998	34.8	12.4	0.00	1.5	0.13	-6.8	0.00	416	1	1.66	570	0.14
2	652	10.9	7111	48.0	9.9	0.00	1.9	0.06	-3.1	0.00	468	1	1.82	652	0.01
3	340	18.9	6424	62.8	12.4	0.00	1.6	0.12	-0.8	0.40	439	1	1.67	340	0.10
4	627	12.6	7870	53.5	11.7	0.00	0.6	0.52	-3.4	0.00	660	2	1.87	342	0.00
5	636	10.5	6657	36.0	14.3	0.00	1.0	0.31	-2.8	0.01	342	1	1.82	636	0.00
6	864	9.3	8005	34.2	11.4	0.00	1.3	0.20	-5.1	0.00	395	2	1.90	486	0.01
7	782	8.7	6825	35.7	9.1	0.00	1.0	0.31	-2.5	0.01	420	1	1.80	782	0.00
8	719	10.4	7469	40.7	9.5	0.00	1.2	0.23	-2.1	0.03	446	2	1.85	407	0.23
9	1035	7.8	8083	25.6	12.2	0.00	0.9	0.35	-10.6	0.00	250	2	1.88	539	0.03
10	687	10.8	7420	47.1	9.7	0.00	2.5	0.01	-2.6	0.01	444	1	1.80	687	0.02
11	561	10.8	6050	34.6	13.7	0.00	1.6	0.11	-1.5	0.15	406	1	1.79	561	0.00
12	990	8.9	8828	40.4	8.1	0.00	1.0	0.34	-5.3	0.00	688	2	1.91	556	0.02
13	759	9.0	6804	20.0	8.3	0.00	2.2	0.03	-9.8	0.00	185	2	1.73	449	0.00
14	680	11.4	7738	38.5	10.8	0.00	2.2	0.02	-4.4	0.00	461	1	1.70	680	0.14
15	223	12.3	2750	58.2	6.8	0.00	3.2	0.00	1.6	0.12	475	1	1.90	223	0.21
16	489	7.3	3568	30.3	5.3	0.00	1.2	0.23	-1.0	0.33	424	2	1.98	282	0.01
17	246	12.1	2967	29.5	10.4	0.00	3.5	0.00	-1.8	0.08	184	1	1.67	246	0.03
18	415	10.6	4393	30.6	10.6	0.00	2.3	0.02	-6.8	0.00	311	1	1.71	415	0.21
19	409	10.8	4416	53.1	8.3	0.00	1.4	0.15	-2.2	0.03	464	1	1.93	409	0.04
20	381	6.6	2505	34.3	6.3	0.00	0.8	0.42	1.0	0.33	396	2	2.19	174	0.03
21	503	10.7	5359	37.2	8.3	0.00	3.2	0.00	-1.1	0.27	332	2	1.80	281	0.11
22	290	13.5	3928	56.1	9.5	0.00	1.8	0.07	-1.4	0.18	501	1	1.85	290	0.01
23	629	12.5	7861	52.3	10.4	0.00	1.4	0.16	-2.3	0.02	501	2	1.87	377	0.20
mean	586	10.8	6088		10.0	0.05>	1.7	0.05>	-3.3	0.05>	418	1.4	1.83	451	0.1<
s.d.	221	2.5	1933		2.3	23	0.8	8	3.0	15	121	0.5	0.1	169	7

n, number of all of the rest bouts; <x>, average length of the rest bout (min); total, total length of rest bout (min); sd, standard deviation of the length of the rest bout (min); LR, log likelihood ratio of the power-law distribution to exponential distribution; p, p-value, positive values of the LR with p<0.05 indicate that the power-law distribution is statistically favored over the alternative distribution. p-values less than 0.05 are indicated in italic. In the power law test, we calculated the p′-value for the best power-law fit for the empirical data set. p′-values larger than 0.1 are indicated in italic. xmax, maximum value of fitted portion; xmin, minimum value of fitted portion; a, exponent of the fitted power law function; ntail, number of bouts with x ≥ xmin.

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