c7cc6f9a65faceb858ad7dba5876eecd *CITATION
aa58aa850af64d590677d104c12017bc *DESCRIPTION
cc0c154ddd7fa7aa5b5024a21df7b053 *INDEX
95354917e69541f73922fa8cd7f96dae *Meta/Rd.rds
14695397f1dc123e41d3398a33b9add6 *Meta/data.rds
8bd78fe4d71c3aeb1a0f4982ee51622b *Meta/features.rds
70124e12e61f1b8ca2df3457841330bd *Meta/hsearch.rds
27151067dd2a84e4363c95aef9b61fe0 *Meta/links.rds
1cd3557c1af678ede16115c235b19fd0 *Meta/nsInfo.rds
67312ddf99c7c8705903517689a93e52 *Meta/package.rds
ac7dc0b40b644a86ccf6958c0d7bce50 *Meta/vignette.rds
a89da460e6698fb94129822e6cfa985e *NAMESPACE
58c2edadf17c0d14a7728967315793a8 *NEWS.md
d6c68f1fe41ced6e98a766a3757313da *R/RoBMA
87cb280c5a405b4e2dc3799926e7583e *R/RoBMA.rdb
5fd667218806fc4e31886af3c9a6961d *R/RoBMA.rdx
5f40973457e0a11b8ec8fa182c05ad88 *README.md
01a328caeac9ab9207e66b5a569aaf0a *REFERENCES.bib
0366efe90ea1181932ed12e772769b20 *WORDLIST
bb4253fc50b5772dcbafae0756498e0b *apa.csl
c3ee6b0991f0d7b1e7e1f35d806104f7 *data/Rdata.rdb
8af846b4d39cd91809c80a30d6a7c8c1 *data/Rdata.rds
5e117924185efe3d174fc9b9874ffe6a *data/Rdata.rdx
3b9dfcf4b55016b2c0ec106bd82df5c8 *doc/index.html
69a8b6a8d72b7b00a75bf55ce3e245fe *doc/v00-introduction.R
6570da154ca062238f46c4a5b2c5c100 *doc/v00-introduction.Rmd
3da21ee6605c339347be93e903ff1545 *doc/v00-introduction.html
5421c5872919fe05170d62409b728d9a *doc/v01-prior-distributions.R
765ce373b661cf53519ad61e5509566c *doc/v01-prior-distributions.Rmd
517c372b4893d4bdd2dd2ab5b5841739 *doc/v01-prior-distributions.html
431dc4e87c54016a2ac88a624ffaa264 *doc/v02-bayesian-meta-analysis.R
4bd320e9affebda6920c6fb9abddd861 *doc/v02-bayesian-meta-analysis.Rmd
6f0ff608c2137a3157f8521afb035d4b *doc/v02-bayesian-meta-analysis.html
926864ad9f099a0d224e68b75a80fbf4 *doc/v03-feature-coverage.R
8f74ef2907c7bb6bf2f92f80dc48eb20 *doc/v03-feature-coverage.Rmd
24bfb31eac81f89f3913bf53f6d3b6b0 *doc/v03-feature-coverage.html
b4daf4ef92385302ae2c81f24e9d80d8 *doc/v10-metafor-parity-multilevel.R
9375babfe1591f7cdf97d446219610f7 *doc/v10-metafor-parity-multilevel.Rmd
b7db5306c629e3e19cb0f6a96ea36ca5 *doc/v10-metafor-parity-multilevel.html
6543e1bbefa4b28c781313249943ae4e *doc/v11-metafor-parity-publication-bias.R
b213ceb6582cc552f28068209354d2e6 *doc/v11-metafor-parity-publication-bias.Rmd
d09272eaea60e9413b459d46a604cbd1 *doc/v11-metafor-parity-publication-bias.html
2611aa3986a7b5ddc73e56cbee928cca *doc/v12-metafor-parity-location-scale.R
f7d385b906540d93553bc44c92ec7bef *doc/v12-metafor-parity-location-scale.Rmd
565259316137f4c7a535c54cecbbfe5e *doc/v12-metafor-parity-location-scale.html
70b9c6a85c72556a0d083f118e77f203 *doc/v13-metafor-parity-glmm.R
b0f5a332dd9922d2772558075528555c *doc/v13-metafor-parity-glmm.Rmd
12c3f32012706b9a02690552df3fd79a *doc/v13-metafor-parity-glmm.html
b51bb152dacce233d746b9a8a60c38ff *doc/v20-bayesian-model-averaging.R
972ac03ea95b3703ab464c63c0034296 *doc/v20-bayesian-model-averaging.Rmd
9792ce21563a9feccc79ac0f1afee338 *doc/v20-bayesian-model-averaging.html
00f05cd44b6648c8f96cc288b64462eb *doc/v21-robust-bayesian-meta-analysis.R
5c1feee4d5df7a15b7bbdd20bc4a70b4 *doc/v21-robust-bayesian-meta-analysis.Rmd
f674ad7cf1a0ee2b80a441c138132b20 *doc/v21-robust-bayesian-meta-analysis.html
3e850edc2d2db41feae74bbb65652aba *doc/v30-tutorial.R
a37c19e88e13dcb92752efc09187fa5d *doc/v30-tutorial.Rmd
af6e02f4926c57766929b2b0d117946d *doc/v30-tutorial.html
0a0cb075a1444fc7c1cca99e65f138a7 *doc/v31-robma-metaregression.R
2646d672affb76339a5c2cdb1b7370f6 *doc/v31-robma-metaregression.Rmd
e3a799ca3d362360fe7835c79398c599 *doc/v31-robma-metaregression.html
17f0814d356a88e877f0536dc55add35 *doc/v32-robma-multilevel.R
346aacc7fc7227e59234cef0441a87ab *doc/v32-robma-multilevel.Rmd
cef24196f995d20ef19f78be281d1b61 *doc/v32-robma-multilevel.html
7d82976b510837f4c38ec2030f989891 *doc/v33-robma-multilevel-metaregression.R
13e70c8b7457fd241c23e6b32f9137cc *doc/v33-robma-multilevel-metaregression.Rmd
b8b41ede5a5a209e5874a624f8105457 *doc/v33-robma-multilevel-metaregression.html
393d42934bedace21f3a301c5b63d197 *doc/v34-bma-norm-medicine.R
a96ac375cf15e974e76d714a94e9724f *doc/v34-bma-norm-medicine.Rmd
aeffc25a3b0bd1712cc054f889881cbd *doc/v34-bma-norm-medicine.html
1b88b3a3f4a219613be45547150320c1 *doc/v35-bma-glmm-medicine.R
6acd0cd4cc1a1aef593f100eb6d69991 *doc/v35-bma-glmm-medicine.Rmd
9ae3883a7194cd82e29e2a738b9f9beb *doc/v35-bma-glmm-medicine.html
2cb08c83309f2366f364bed2400747b9 *doc/v36-zplot.R
016d9f51114ed81c3783f0732b9ccffa *doc/v36-zplot.Rmd
23d5e8b9d57c4da25e568951f60a4d69 *doc/v36-zplot.html
4d211b14e39ec4a3aafdc8c2e1c689c9 *help/AnIndex
b7cdd1b4ed2c1cd3e1d03a5f9e97141b *help/RoBMA.rdb
149645a02e183716c240a6b3576001da *help/RoBMA.rdx
fd236171330071654b91e02c32c7350a *help/aliases.rds
efa2d59e57efb92c56816c68f0ad8cdb *help/figures/README-fig_PETPEESE-1.png
d0ae99e8306e0b46da9ce904ec38371a *help/figures/README-fig_forest-1.png
377d02929e96024adb04f1fcaf6d3550 *help/figures/README-fig_mu-1.png
714a4e58cf012010fb66b2c09126cd64 *help/figures/README-fig_mu_chain-1.png
013a1676deb02afd88773ceff2f45723 *help/figures/README-fig_mu_ind-1.png
376bd742745f3a1c5108c0e2848569d0 *help/figures/README-fig_omega-1.png
fdb65ba191664bbb37b64edf6f10d561 *help/figures/README-fig_tau-1.png
8358177fae27f491ee3bdf9331c697bf *help/figures/README-fig_weightfunction-1.png
a4fce634637c7adc56d68b38c9379e35 *help/paths.rds
df6a3c01c78aa37061ac1d67c5e39a0e *html/00Index.html
ee41876c0116916bb04bcf4fe3e43d78 *html/R.css
ebede6206429ef611db4ffc2b812a7e6 *libs/x64/RoBMA.dll
a0e061f6c9bab2271f7890912417acfb *libs/x64/symbols.rds
