The goal of metabroom is to broom
meta-analysis models produced by
metafor
. That is, when I finish it.
See the testing file to see where I’m at.
# Hmmm. What's best practice for loading %>% in packages? What's best practice for package dependencies?
library(metabroom)
# Check all is as it should be.
example_ma %>%
metafor::forest()
augment
example_ma %>% augment()
#> # A tibble: 9 x 7
#> .rownames y .fitted .se.fit conf.low.fit conf.high.fit .resid
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Edinburgh -0.355 -0.358 0.113 -0.581 -0.136 0.182
#> 2 Orpington-Mild -0.348 -0.362 0.245 -0.843 0.118 0.189
#> 3 Orpington-Moder… -2.32 -2.22 0.209 -2.63 -1.81 -1.78
#> 4 Orpington-Severe -1.89 -1.66 0.369 -2.38 -0.937 -1.35
#> 5 Montreal-Home -0.384 -0.416 0.409 -1.22 0.386 0.153
#> 6 Montreal-Transf… 0.172 0.141 0.188 -0.229 0.510 0.709
#> 7 Newcastle 0.272 0.215 0.238 -0.251 0.681 0.809
#> 8 Umea -0.425 -0.427 0.121 -0.664 -0.190 0.113
#> 9 Uppsala 0.290 0.253 0.187 -0.113 0.619 0.827
tidy
example_ma %>% tidy()
#> # A tibble: 10 x 8
#> study type estimate std.error statistic p.value conf.low conf.high
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Edinburgh study -0.355 0.114 -3.11 NA -0.579 -0.131
#> 2 Orpington… study -0.348 0.254 -1.37 NA -0.846 0.150
#> 3 Orpington… study -2.32 0.214 -10.8 NA -2.74 -1.90
#> 4 Orpington… study -1.89 0.401 -4.71 NA -2.67 -1.10
#> 5 Montreal-… study -0.384 0.453 -0.847 NA -1.27 0.504
#> 6 Montreal-… study 0.172 0.192 0.896 NA -0.204 0.549
#> 7 Newcastle study 0.272 0.245 1.11 NA -0.209 0.753
#> 8 Umea study -0.425 0.122 -3.48 NA -0.664 -0.186
#> 9 Uppsala study 0.290 0.190 1.52 NA -0.0837 0.663
#> 10 overall summ… -0.537 0.309 -1.74 0.0818 -1.14 0.0679
glance
example_ma %>% glance()
#> # A tibble: 1 x 16
#> k measure method i.squared h.squared tau.squared tau.squared.se QE
#> <int> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 9 SMD REML 95.5 22.2 0.791 0.428 124.
#> # … with 8 more variables: QE_p <dbl>, QM <dbl>, QM_p <dbl>, logLik <dbl>,
#> # deviance <dbl>, AIC <dbl>, BIC <dbl>, AICc <dbl>
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