Samples were drawn using sampling(NUTS). For each parameter, Bulk_ESS and Tail_ESS are effective sample size measures, and Rhat is the potential scale reduction factor on split chains (at convergence, Rhat = 1). ################################## #ariaDNE 0.08 (ep_08) > summary(ep08_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.84 0.57 2.81 5.05 1.00 8562 6304 sd(muIN_Intercept) 2.63 0.60 1.57 3.91 1.00 7520 5693 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.89 1.03 -4.00 0.05 1.00 4420 5792 muIN_Intercept -3.44 1.05 -5.70 -1.54 1.00 5334 5264 muFL_ep_08 1.12 0.80 -0.43 2.72 1.00 7930 6991 muIN_ep_08 3.93 1.09 1.98 6.24 1.00 6800 5714 ################################## #ariaDNE 0.08 (ep_08) + OPC > summary(ep08_opc_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + OPC + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.77 0.59 2.71 5.00 1.00 10186 6573 sd(muIN_Intercept) 2.65 0.60 1.57 3.93 1.00 7403 5706 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.83 1.03 -3.93 0.09 1.00 4531 5449 muIN_Intercept -3.79 1.16 -6.23 -1.71 1.00 5060 5288 muFL_ep_08 0.95 0.86 -0.72 2.68 1.00 8690 6578 muFL_OPC 1.16 0.74 -0.21 2.71 1.00 7477 5700 muIN_ep_08 4.28 1.18 2.16 6.78 1.00 7024 5448 muIN_OPC -0.44 0.84 -2.13 1.18 1.00 8189 6220 ################################## #ariaDNE 0.08 (ep_08) + RFI > summary(ep08_rfi_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + RFI + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.89 0.57 2.85 5.08 1.00 8022 5691 sd(muIN_Intercept) 2.71 0.60 1.62 3.96 1.00 7407 5003 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.91 1.04 -4.08 0.08 1.00 4014 5315 muIN_Intercept -3.59 1.10 -5.95 -1.62 1.00 5735 4962 muFL_ep_08 1.19 0.96 -0.67 3.14 1.00 7481 6046 muFL_RFI -0.09 0.76 -1.57 1.42 1.00 7074 5956 muIN_ep_08 3.99 1.20 1.81 6.54 1.00 6739 5070 muIN_RFI 0.12 0.85 -1.58 1.78 1.00 6274 5851 ################################## #ariaDNE 0.08 (ep_08) + ariaDNE 0.08 CV (ep_08_sd) > summary(ep08_sd_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + ep_08_sd + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.69 0.57 2.66 4.86 1.00 8970 6608 sd(muIN_Intercept) 2.32 0.60 1.26 3.59 1.00 7545 5958 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.88 1.02 -3.97 0.09 1.00 4641 5394 muIN_Intercept -4.63 1.29 -7.37 -2.26 1.00 4529 3706 muFL_ep_08 1.24 0.82 -0.33 2.90 1.00 7682 5916 muFL_ep_08_sd 1.45 0.82 -0.01 3.21 1.00 8960 5240 muIN_ep_08 4.68 1.21 2.43 7.20 1.00 5641 4853 muIN_ep_08_sd -1.97 1.09 -4.19 0.09 1.00 5443 5224 ################################## #ariaDNE 0.08 (ep_08) + ariaDNE 0.08 CV (ep_08_sd) + OPC > summary(ep08_sd_opc_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + ep_08_sd + OPC + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.63 0.58 2.58 4.83 1.00 9766 6277 sd(muIN_Intercept) 2.38 0.61 1.30 3.65 1.00 8368 5467 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.90 1.03 -4.03 0.01 1.00 5196 5892 muIN_Intercept -4.78 1.29 -7.47 -2.47 1.00 6313 5615 muFL_ep_08 1.08 0.88 -0.60 2.85 1.00 8368 6284 muFL_ep_08_sd 1.56 0.86 0.01 3.38 1.00 9715 6176 muFL_OPC 1.30 0.78 -0.13 2.89 1.00 8578 6178 muIN_ep_08 4.84 1.22 2.66 7.42 1.00 7579 5700 muIN_ep_08_sd -1.94 1.12 -4.20 0.20 1.00 7505 6278 muIN_OPC -0.28 0.86 -2.02 1.37 1.00 10083 6510 ################################## #ariaDNE 0.08 (ep_08) + ariaDNE 0.08 CV (ep_08_sd) + RFI > summary(ep08_sd_rfi_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + ep_08_sd + RFI + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.74 0.58 2.71 4.95 1.00 7011 5751 sd(muIN_Intercept) 2.33 0.63 1.20 3.63 1.00 5744 4620 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.91 1.05 -4.03 0.07 1.00 3965 4458 muIN_Intercept -4.67 1.27 -7.34 -2.35 1.00 4027 4490 muFL_ep_08 1.14 0.98 -0.75 3.07 1.00 6145 5802 muFL_ep_08_sd 1.56 0.88 -0.03 3.43 1.00 7030 5809 muFL_RFI 0.23 0.82 -1.29 1.88 1.00 5628 5364 muIN_ep_08 4.93 1.30 2.51 7.63 1.00 4534 5106 muIN_ep_08_sd -2.05 1.13 -4.35 0.09 1.00 4744 4491 muIN_RFI -0.29 0.85 -1.95 1.36 1.00 5688 5407 ################################## #ariaDNE 0.08 (ep_08) + ariaDNE 0.08 CV (ep_08_sd) + OPC + RFI > summary(ep08_sd_opc_rfi_mod, WAIC=T) Family: categorical Links: muFL = logit; muIN = logit Formula: diet ~ ep_08 + ep_08_sd + OPC + RFI + (1 | genus) Data: data (Number of observations: 222) Samples: 4 chains, each with iter = 3000; warmup = 1000; thin = 1; total post-warmup samples = 8000 Group-Level Effects: ~genus (Number of levels: 22) Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS sd(muFL_Intercept) 3.69 0.58 2.66 4.89 1.00 8691 6143 sd(muIN_Intercept) 2.35 0.64 1.19 3.70 1.00 5800 3782 Population-Level Effects: Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS muFL_Intercept -1.87 1.04 -4.01 0.05 1.00 4668 5312 muIN_Intercept -4.84 1.30 -7.56 -2.47 1.00 5874 5886 muFL_ep_08 0.76 1.07 -1.36 2.83 1.00 6114 5811 muFL_ep_08_sd 1.75 0.94 0.12 3.74 1.00 7894 5589 muFL_OPC 1.42 0.82 -0.07 3.08 1.00 6281 5680 muFL_RFI 0.53 0.87 -1.11 2.27 1.00 5924 4883 muIN_ep_08 5.17 1.33 2.71 7.94 1.00 4954 6054 muIN_ep_08_sd -2.07 1.14 -4.34 0.12 1.00 5589 6273 muIN_OPC -0.31 0.90 -2.09 1.39 1.00 8495 6287 muIN_RFI -0.34 0.87 -2.06 1.39 1.00 5598 5290