A Copula Type-Model for Examining the Role of Microbiome as a Potential Tool in Diagnosis

Table 9

Parameter estimates (first row) and values (second row) for the regressors associated with the six predictors for individuals classified as nonsedentary (bivariate regression model).

		Predictor 1	Predictor 2	Predictor 3	Predictor 4	Predictor 5	Predictor 6
Age	Group 1	−0.0256	—	0.1122	−0.0160	−0.0783	0.0123
		0.6443	—	0.1419	0.8252	0.3330	0.8009
	Group 2	−0.1632	−0.1279	—	−0.1313	−0.1980	−0.1032
		0.0076	0.0952	—	0.0478	0.0317	0.0493
	Group 3	−0.0324	0.0075	0.1344	—	−0.0650	0.0283
		0.5360	0.9174	0.0425	—	0.3906	0.5205
	Group 4	0.0353	0.0749	0.1917	0.0617	—	0.0913
		0.5767	0.3550	0.0371	0.4146	—	0.1690
	Group 5	−0.0546	−0.0205	0.1022	−0.0299	−0.0950	—
		0.1714	0.6748	0.0513	0.4980	0.1527	—
	Group 0	—	0.0420	0.1640	0.0323	−0.0328	0.0622
		—	0.4480	0.0072	0.5383	0.6037	0.1197
	Intercept	−0.2207	−0.1789	−0.1543	−0.1667	−0.1726	−0.1595
		0.1532	0.2471	0.3170	0.2802	0.2636	0.3015
		2.9231	2.9215	2.9357	2.9269	2.9234	2.9294
		BMI	Group 1	0.0183	—	0.1122	0.0182	0.1886	0.0139
0.8906	—			0.1419	0.9198	0.3338	0.9090
Group 2	−0.1063		−0.1419	—	−0.1120	0.0545	−0.1103
	0.4730		0.4582	—	0.4883	0.8052	0.3944
Group 3	0.0070		−0.0286	0.1344	—	0.1682	0.0003
	0.9561		0.8746	0.0426	—	0.3537	0.9933
Group 4	−0.1635		−0.1953	−0.0549	−0.1703	—	−0.1644
	0.2825		0.3168	0.8036	0.3474	—	0.2959
Group 5	0.0037		−0.0281	0.1133	−0.0023	0.1680	—
	0.9687		0.8168	0.3815	0.9831	0.2856	—
Group 0	—		−0.0344	0.1074	−0.0067	0.1623	−0.0054
	—		0.7963	0.4682	0.9576	0.2860	0.9546
Intercept	0.2518		0.2081	0.2263	0.2352	0.2327	0.2471
	0.5380		0.6100	0.5790	0.5641	0.5689	0.5455
	23.8809		23.8742	23.8818	23.8866	23.8793	23.8795
			31.2662	31.2593	31.2647	31.2716	31.2667	31.2640
			1.9226	1.9203	0.9188	1.9169	1.9224	1.9238
			1.4653	1.4656	1.4624	1.4634	1.4665	1.4655
			0.1970	0.1968	0.1965	0.1968	0.1970	0.1967
			114.9900	110.6990	98.4523	103.0250	110.6760	106.2180
0.5978			0.5840	0.5393	0.5879	0.5816	0.5676