I ran the model using the above priors. The good thing is that I got simplex results. However, the Rhats are not good.
here is the results
Data: bodi (Number of observations: 2622)
Samples: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
total post-warmup samples = 4000
Group-Level Effects:
~idno (Number of levels: 898)
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
sd(Intercept) 4.13 0.14 3.86 4.41 1.01 457 1116
Population-Level Effects:
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
Intercept[1] -11.12 0.50 -12.11 -10.17 1.01 949 1834
Intercept[2] -8.07 0.30 -8.67 -7.51 1.01 703 1816
Intercept[3] -5.67 0.21 -6.10 -5.28 1.02 422 1057
Intercept[4] -3.56 0.18 -3.92 -3.20 1.03 262 803
Intercept[5] -1.82 0.17 -2.15 -1.50 1.04 219 514
Intercept[6] -0.06 0.16 -0.38 0.24 1.04 125 498
Intercept[7] 1.40 0.16 1.08 1.71 1.04 130 560
Intercept[8] 2.97 0.17 2.64 3.30 1.03 172 687
Intercept[9] 4.49 0.19 4.13 4.87 1.03 259 983
Intercept[10] 5.97 0.21 5.57 6.40 1.02 373 1267
Intercept[11] 7.60 0.25 7.14 8.08 1.02 554 1719
Intercept[12] 9.49 0.31 8.92 10.10 1.01 650 2034
Intercept[13] 11.21 0.41 10.43 12.04 1.01 1412 2826
Intercept[14] 13.22 0.66 12.04 14.59 1.00 2611 2885
mochf 0.50 0.08 0.34 0.65 1.00 915 1622
Simplex Parameters:
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
mochf1[1] 0.16 0.09 0.03 0.36 1.00 2083 2314
mochf1[2] 0.84 0.09 0.64 0.97 1.00 2083 2314
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).
The good news is I got the simplex result but not good Rhat
Should I change the priors’ values?
Thanks