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View Code? Open in Web Editor NEWBayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Home Page: https://danheck.github.io/metaBMA/
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yunglymetabma's Issues
plot_forest: cex.axis not altering size of the effect size axis labels
The cex.axis argument appears to not be successfully altering the size of the effect size axis labels.
In plot_forest.default, for the cex.axis argument to influence the effect size axis size, the cex.axis parameter needs to be passed to its plot command:
plot(
x = Effect, y = -100, xlim = range(xxx),
yaxt = "n", ylab = "", las = 1,
ylim = c(-n.ests, n.studies),
bty = "n", ...
)
changing `ci` value doesn't change posterior estimates
The documentation mentions-
But changing the value of ci, doesn't seem to change estimates in the output. Is this by design?
library(metaBMA)
#> Loading required package: Rcpp
data(towels)
# default
set.seed(123)
mr <-
meta_random(
logOR,
SE,
study,
data = towels,
ci = 0.95
)
#> Warning: There were 4 divergent transitions after warmup. See
#> http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them.
#> Warning: Examine the pairs() plot to diagnose sampling problems
mr$estimates
#> mean sd 2.5% 50% 97.5% hpd95_lower
#> d 0.1820016 0.10363018 -0.03902097 0.1877645 0.3670940 -0.02095039
#> tau 0.1355887 0.09893691 0.03348296 0.1081037 0.4037003 0.02027280
#> hpd95_upper n_eff Rhat
#> d 0.3811258 3974.8 1
#> tau 0.3296088 3145.4 1
# change ci value
set.seed(123)
mr <-
meta_random(
logOR,
SE,
study,
data = towels,
ci = 0.99
)
#> Warning: There were 4 divergent transitions after warmup. See
#> http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them.
#> Warning: Examine the pairs() plot to diagnose sampling problems
mr$estimates
#> mean sd 2.5% 50% 97.5% hpd95_lower
#> d 0.1820016 0.10363018 -0.03902097 0.1877645 0.3670940 -0.02095039
#> tau 0.1355887 0.09893691 0.03348296 0.1081037 0.4037003 0.02027280
#> hpd95_upper n_eff Rhat
#> d 0.3811258 3974.8 1
#> tau 0.3296088 3145.4 1Robustness check
Is it possible to add a priors robusteness check?
Update dev or README
The dev branch is behind the master one; in the README is suggested to install w/ ref = "dev" for the development version (supposed to be more updated than the master/CRAN one), but that way the version installed is the 0.6.0.
On the other hand, installing from GitHub w/o ref = "dev" will install the master branch release, which corresponds to the last, now, 0.6.2 package version.
Suggestions: remove the indication "ref = dev" from README, or merge master into dev.
changing the prior default to `cauchy(0, 0.707)`
Context: easystats/parameters#347 (comment)
Maybe also leave out the internal numbers rscale_contin and rscale_discrete to avoid this confusion? At least until the moderator analysis is implemented.
Will you be open to having another quick release with these changes in the near future (pre-Christmas)?
feature request: supporting methods to compute centrality and credible intervals for estimates
Currently, metaBMA by default returns mean + HDIs:
library(metaBMA)
#> Loading required package: Rcpp
#> This is metaBMA version 0.6.6
#> - Default priors were changed in version 0.6.6.
#> - Since default priors may change again, it is safest to specify priors (even when using the defaults).
data(towels)
set.seed(123)
mb <- meta_bma(logOR, SE, study, towels)
#> Warning: There were 2 divergent transitions after warmup. See
#> http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them.
#> Warning: Examine the pairs() plot to diagnose sampling problems
mb$estimates
#> mean sd 2.5% 50% 97.5% hpd95_lower
#> averaged 0.2145214 0.0882580 0.03546521 0.2165312 0.3813311 0.03963277
#> fixed 0.2208839 0.0783599 0.06556325 0.2219074 0.3747273 0.06047198
#> random 0.1988286 0.1062576 -0.02208767 0.2023509 0.3949067 -0.01460747
#> hpd95_upper n_eff Rhat
#> averaged 0.3846720 NA NA
#> fixed 0.3662384 3485.5 1
#> random 0.3995670 5359.7 1Created on 2021-01-15 by the reprex package (v0.3.0)
Session info
devtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.0.3 (2020-10-10)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin17.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Berlin
#> date 2021-01-15
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2)
#> bridgesampling 1.0-0 2020-02-26 [1] CRAN (R 4.0.2)
#> Brobdingnag 1.2-6 2018-08-13 [1] CRAN (R 4.0.2)
#> callr 3.5.1 2020-10-13 [1] CRAN (R 4.0.2)
#> cli 2.2.0 2020-11-20 [1] CRAN (R 4.0.3)
#> coda 0.19-4 2020-09-30 [1] CRAN (R 4.0.2)
#> codetools 0.2-16 2018-12-24 [2] CRAN (R 4.0.3)
#> colorspace 2.0-0 2020-11-11 [1] CRAN (R 4.0.2)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.2)
#> curl 4.3 2019-12-02 [1] CRAN (R 4.0.1)
#> desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.2)
#> devtools 2.3.2 2020-09-18 [1] CRAN (R 4.0.2)
#> digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.2)
#> dplyr 1.0.2 2020-08-18 [1] CRAN (R 4.0.2)
#> ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.2)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.1)
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.2)
#> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
#> generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.2)
#> ggplot2 3.3.3 2020-12-30 [1] CRAN (R 4.0.3)
#> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
#> gridExtra 2.3 2017-09-09 [1] CRAN (R 4.0.2)
#> gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.2)
#> highr 0.8 2019-03-20 [1] CRAN (R 4.0.2)
#> htmltools 0.5.1 2021-01-12 [1] CRAN (R 4.0.3)
#> inline 0.3.17 2020-12-01 [1] CRAN (R 4.0.3)
#> jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.0.3)
#> knitr 1.30 2020-09-22 [1] CRAN (R 4.0.2)
#> LaplacesDemon 16.1.4 2020-02-06 [1] CRAN (R 4.0.2)
#> lattice 0.20-41 2020-04-02 [2] CRAN (R 4.0.3)
#> lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.2)
#> logspline 2.1.16 2020-05-08 [1] CRAN (R 4.0.2)
#> loo 2.4.1 2020-12-09 [1] CRAN (R 4.0.3)
#> magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.0.3)
#> Matrix 1.2-18 2019-11-27 [2] CRAN (R 4.0.3)
#> matrixStats 0.57.0 2020-09-25 [1] CRAN (R 4.0.2)
#> memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.2)
#> metaBMA * 0.6.6 2021-01-08 [1] CRAN (R 4.0.3)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2)
#> mvtnorm 1.1-1 2020-06-09 [1] CRAN (R 4.0.2)
#> pillar 1.4.7 2020-11-20 [1] CRAN (R 4.0.3)
#> pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.0.3)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
#> pkgload 1.1.0 2020-05-29 [1] CRAN (R 4.0.2)
#> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.2)
#> processx 3.4.5 2020-11-30 [1] CRAN (R 4.0.3)
#> ps 1.5.0 2020-12-05 [1] CRAN (R 4.0.3)
#> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.2)
#> R6 2.5.0 2020-10-28 [1] CRAN (R 4.0.2)
#> Rcpp * 1.0.5 2020-07-06 [1] CRAN (R 4.0.2)
#> RcppParallel 5.0.2 2020-06-24 [1] CRAN (R 4.0.2)
#> remotes 2.2.0 2020-07-21 [1] CRAN (R 4.0.2)
#> rlang 0.4.10 2020-12-30 [1] CRAN (R 4.0.3)
#> rmarkdown 2.6 2020-12-14 [1] CRAN (R 4.0.3)
#> rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.0.3)
#> rstan 2.21.2 2020-07-27 [1] CRAN (R 4.0.3)
#> rstantools 2.1.1 2020-07-06 [1] CRAN (R 4.0.2)
#> scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.2)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
#> StanHeaders 2.21.0-7 2020-12-17 [1] CRAN (R 4.0.3)
#> stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.2)
#> testthat 3.0.1 2020-12-17 [1] CRAN (R 4.0.3)
#> tibble 3.0.4 2020-10-12 [1] CRAN (R 4.0.2)
#> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2)
#> usethis 2.0.0 2020-12-10 [1] CRAN (R 4.0.3)
#> V8 3.4.0 2020-11-04 [1] CRAN (R 4.0.2)
#> vctrs 0.3.6 2020-12-17 [1] CRAN (R 4.0.3)
#> withr 2.3.0 2020-09-22 [1] CRAN (R 4.0.2)
#> xfun 0.20 2021-01-06 [1] CRAN (R 4.0.3)
#> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.2)
#>
#> [1] /Users/patil/Library/R/4.0/library
#> [2] /Library/Frameworks/R.framework/Versions/4.0/Resources/libraryBut I was wondering if you would be willing to support two additional arguments:
- centrality: The point-estimate (centrality index) to compute. Character (vector) of one of these options:
"median","mean"(current default), or"MAP". - ci_method: The type of index used for Credible Interval. Can be
"HDI","ETI"(https://easystats.github.io/bayestestR/reference/eti.html), or"SI"(https://easystats.github.io/bayestestR/reference/si.html).
error in load action .__A__.1 for package metaBMA: is(module, "character"): object 'm' not found
Trouble loading the new version (0.6.3) of metaBMA package on a Windows machine:
> packageVersion("metaBMA")
[1] ‘0.6.3’
> library(metaBMA)
Loading required package: Rcpp
Error: package or namespace load failed for ‘metaBMA’ in .doLoadActions(where, attach):
error in load action .__A__.1 for package metaBMA: is(module, "character"): object 'm' not foundThis is the trace I see:
> traceback()
6: stop(msg, call. = FALSE, domain = NA)
5: value[[3L]](cond)
4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
3: tryCatchList(expr, classes, parentenv, handlers)
2: tryCatch({
attr(package, "LibPath") <- which.lib.loc
ns <- loadNamespace(package, lib.loc)
env <- attachNamespace(ns, pos = pos, deps, exclude, include.only)
}, error = function(e) {
P <- if (!is.null(cc <- conditionCall(e)))
paste(" in", deparse(cc)[1L])
else ""
msg <- gettextf("package or namespace load failed for %s%s:\n %s",
sQuote(package), P, conditionMessage(e))
if (logical.return)
message(paste("Error:", msg), domain = NA)
else stop(msg, call. = FALSE, domain = NA)
})
1: library(metaBMA)Here is session info:
> sessioninfo::session_info(include_base = TRUE)
- Session info ---------------------------------------------------------------------------------------------------------------------------
setting value
version R Under development (unstable) (2020-02-28 r77874)
os Windows 10 x64
system x86_64, mingw32
ui RStudio
language (EN)
collate English_United States.1252
ctype English_United States.1252
tz Europe/Berlin
date 2020-06-04
- Packages -------------------------------------------------------------------------------------------------------------------------------
! package * version date lib source
assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0)
base * 4.0.0 2020-02-29 [?] local
cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.0)
P compiler 4.0.0 2020-02-29 [2] local
crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.0)
P datasets * 4.0.0 2020-02-29 [2] local
digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.0)
evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.0)
fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.0)
glue 1.4.1 2020-05-13 [1] CRAN (R 4.0.0)
P graphics * 4.0.0 2020-02-29 [2] local
P grDevices * 4.0.0 2020-02-29 [2] local
htmltools 0.4.0 2019-10-04 [1] CRAN (R 4.0.0)
knitr 1.28 2020-02-06 [1] CRAN (R 4.0.0)
P methods * 4.0.0 2020-02-29 [2] local
Rcpp 1.0.4.6 2020-04-09 [1] CRAN (R 4.0.0)
rlang 0.4.6 2020-05-02 [1] CRAN (R 4.0.0)
rmarkdown 2.2 2020-05-31 [1] CRAN (R 4.0.0)
rstudioapi 0.11 2020-02-07 [1] CRAN (R 4.0.0)
sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.0)
P stats * 4.0.0 2020-02-29 [2] local
P tools 4.0.0 2020-02-29 [2] local
P utils * 4.0.0 2020-02-29 [2] local
withr 2.2.0 2020-04-20 [1] CRAN (R 4.0.0)
xfun 0.14 2020-05-20 [1] CRAN (R 4.0.0)
yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)
[1] C:/Users/inp099/Documents/R/win-library/4.0
[2] C:/Program Files/R/R-devel/library
P -- Loaded and on-disk path mismatch.error loading library in MacOS Catalina
Hi!
I have installed your package both from CRAN version and developer GitHub version, but when trying to load it in my R session via library(metaBMA) I keep getting this error:
Loading required package: Rcpp
Error: package or namespace load failed for ‘metaBMA’ in .doLoadActions(where, attach):
error in load action .A.1 for package metaBMA: is(module, "character"): object 'm' not found
Do you have any idea what could be wrong or how to solve it?
Thanks in advance!
Compilation error
I try to build metaBMA using R 4.0.0 running on Unbuntu 18.04LTS (gcc 5.4.0) but it fails with the following error..
/home/user/R/x86_64-pc-linux-gnu-library/4.0/StanHeaders/include/stan/math/rev/mat/functor/adj_jac_apply.hpp:619:15: error: invalid use of ‘auto’ return (*vi)(args...); ^
I understand that it is possibly related to stan, still rstan package compile very well.. Any idea ?
thx.
plot_forest: 'main' doesn't let you change the plot title text
I would like to change the title text of the plot generated by plot_forest, but using the main argument does not work because it is hard-coded here instead of being passed in from the main call:
plot_forest.default(meta,
from = from, to = to, summary = summary,
shrinked = shrinked, cex.axis = cex.axis,
main = "Meta-Analysis with Model-Averaging", ...
)
Example:
> plot_forest(fit_BMA_test, shrinked ="",
+ mar = c(4.5, 25, 4, 0.3),
+ cex.axis = 2,
+ cex.main = 2,
+ cex.lab = 2, main="Test")
Error in plot.default(x = Effect, y = -100, xlim = range(xxx), yaxt = "n", :
formal argument "main" matched by multiple actual arguments
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