Nothing
Code
extract.modmed.mlm.brms(fit.randa, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.417 0.416 0.0396 0.0394 0.343 0.496 1.00 1904. 2675.
Code
extract.modmed.mlm.brms(fit.randb, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.379 0.378 0.0370 0.0367 0.311 0.454 1.00 1851. 2792.
Code
extract.modmed.mlm.brms(fit.randboth, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.452 0.449 0.0527 0.0519 0.355 0.562 1.00 3377. 3165.
Code
extract.modmed.mlm.brms(fit.randall, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.460 0.457 0.0545 0.0540 0.362 0.574 1.00 3595. 4071.
Code
extract.modmed.mlm.brms(fitmoda, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.207 0.202 0.0595 0.0561 0.105 0.338 1.00 1869. 2495.
Code
extract.modmed.mlm.brms(fitmoda, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.249 0.245 0.0644 0.0622 0.140 0.392 1.00 1831. 2450.
Code
extract.modmed.mlm.brms(fitmoda, "indirect", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.207 0.202 0.0595 0.0561 0.105 0.338 1.00 1869. 2495.
Code
extract.modmed.mlm.brms(fitmodb, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.305 0.297 0.0722 0.0676 0.183 0.466 1.00 1376. 2114.
Code
extract.modmed.mlm.brms(fitmodb, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.189 0.183 0.0569 0.0531 0.0940 0.315 1.00 1445. 2277.
Code
extract.modmed.mlm.brms(fitmodb, "indirect", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.305 0.297 0.0722 0.0676 0.183 0.466 1.00 1376. 2114.
Code
extract.modmed.mlm.brms(fitmodab, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.270 0.264 0.0673 0.0653 0.153 0.414 1.00 1755. 2173.
Code
extract.modmed.mlm.brms(fitmodab, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.200 0.195 0.0573 0.0571 0.101 0.324 1.00 1841. 2783.
Code
extract.modmed.mlm.brms(fitmodab, "indirect.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect.di~ 0.0699 0.0692 0.0319 0.0316 0.00913 0.134 1.00 3093. 2994.
Code
extract.modmed.mlm.brms(fitmodab, "a")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.285 0.287 0.0746 0.0762 0.138 0.425 1.00 1872. 2625.
Code
extract.modmed.mlm.brms(fitmodab, "a", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.400 0.401 0.0719 0.0719 0.255 0.539 1.00 1856. 2509.
Code
extract.modmed.mlm.brms(fitmodab, "a.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a.diff -0.115 -0.116 0.0485 0.0483 -0.209 -0.0225 1.00 9128. 3107.
Code
extract.modmed.mlm.brms(fitmodab, "b")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.540 0.540 0.0818 0.0816 0.378 0.700 1.00 2026. 2436.
Code
extract.modmed.mlm.brms(fitmodab, "b", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.210 0.208 0.0801 0.0778 0.0541 0.372 1.00 2147. 2347.
Code
extract.modmed.mlm.brms(fitmodab, "b.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b.diff 0.330 0.329 0.0415 0.0410 0.249 0.412 1.00 7588. 3054.
Code
extract.modmed.mlm.brms(fitmodab2, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.289 0.282 0.0651 0.0632 0.175 0.429 1.00 1575. 2408.
Code
extract.modmed.mlm.brms(fitmodab2, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.167 0.163 0.0608 0.0595 0.0624 0.295 1.00 1952. 2414.
Code
extract.modmed.mlm.brms(fitmodab2, "indirect.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect.diff 0.121 0.119 0.0450 0.0427 0.0371 0.215 1.00 2731. 2848.
Code
extract.modmed.mlm.brms(fitmodab2, "a")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.289 0.289 0.0690 0.0692 0.152 0.418 1.00 1533. 2508.
Code
extract.modmed.mlm.brms(fitmodab2, "a", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.389 0.391 0.0846 0.0839 0.223 0.550 1.00 1741. 2579.
Code
extract.modmed.mlm.brms(fitmodab2, "a.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a.diff -0.0996 -0.0991 0.0714 0.0701 -0.237 0.0428 1.00 2846. 3004.
Code
extract.modmed.mlm.brms(fitmodab2, "b")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.538 0.537 0.0795 0.0782 0.380 0.697 1.00 1560. 2215.
Code
extract.modmed.mlm.brms(fitmodab2, "b", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.215 0.216 0.0789 0.0775 0.0594 0.368 1.00 1645. 2359.
Code
extract.modmed.mlm.brms(fitmodab2, "b.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b.diff 0.323 0.322 0.0418 0.0430 0.241 0.403 1.00 6088. 3413.
Code
extract.modmed.mlm.brms(fitmodab3, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.277 0.269 0.0708 0.0677 0.159 0.433 1.00 1188. 1855.
Code
extract.modmed.mlm.brms(fitmodab3, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.193 0.188 0.0658 0.0610 0.0762 0.343 1.00 1536. 2218.
Code
extract.modmed.mlm.brms(fitmodab3, "indirect.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect.di~ 0.0842 0.0813 0.0557 0.0527 -0.0171 0.202 1.00 1828. 2718.
Code
extract.modmed.mlm.brms(fitmodab3, "a")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.282 0.283 0.0780 0.0786 0.128 0.434 1.00 1212. 1985.
Code
extract.modmed.mlm.brms(fitmodab3, "a", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.402 0.404 0.0746 0.0729 0.252 0.549 1.00 1244. 2255.
Code
extract.modmed.mlm.brms(fitmodab3, "a.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a.diff -0.120 -0.120 0.0487 0.0480 -0.215 -0.0231 1.00 4625. 2999.
Code
extract.modmed.mlm.brms(fitmodab3, "b")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.572 0.572 0.0754 0.0736 0.421 0.718 1.00 1293. 1840.
Code
extract.modmed.mlm.brms(fitmodab3, "b", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.226 0.226 0.0909 0.0894 0.0464 0.400 1.00 1610. 2264.
Code
extract.modmed.mlm.brms(fitmodab3, "b.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b.diff 0.346 0.346 0.0781 0.0782 0.194 0.500 1.00 2089. 2632.
Code
extract.modmed.mlm.brms(fitmodab4, "indirect")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.283 0.277 0.0638 0.0612 0.178 0.426 1.00 1217. 2245.
Code
extract.modmed.mlm.brms(fitmodab4, "indirect", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect 0.164 0.159 0.0716 0.0686 0.0377 0.314 1.00 1562. 2527.
Code
extract.modmed.mlm.brms(fitmodab4, "indirect.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 indirect.di~ 0.119 0.118 0.0627 0.0593 -6.82e-4 0.246 1.00 1965. 2727.
Code
extract.modmed.mlm.brms(fitmodab4, "a")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.287 0.288 0.0693 0.0676 0.150 0.425 1.00 1298. 2323.
Code
extract.modmed.mlm.brms(fitmodab4, "a", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 0.394 0.393 0.0867 0.0854 0.221 0.561 1.00 1623. 2346.
Code
extract.modmed.mlm.brms(fitmodab4, "a.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a.diff -0.106 -0.106 0.0728 0.0720 -0.253 0.0359 1.00 2485. 2941.
Code
extract.modmed.mlm.brms(fitmodab4, "b")$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.568 0.568 0.0755 0.0748 0.425 0.717 1.00 1655. 2542.
Code
extract.modmed.mlm.brms(fitmodab4, "b", modval1 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b 0.236 0.235 0.0910 0.0901 0.0590 0.414 1.00 1644. 2662.
Code
extract.modmed.mlm.brms(fitmodab4, "b.diff", modval1 = 0, modval2 = 1)$CI
Output
# A tibble: 1 x 10
variable mean median sd mad q2.5 q97.5 rhat ess_bulk ess_tail
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 b.diff 0.332 0.333 0.0777 0.0771 0.177 0.484 1.00 2020. 2693.
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