metafor: Interfaces for metafor package for data science pipelines.

In intubate: Interface to Popular R Functions for Data Science Pipelines

Description

Interfaces to metafor functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_escalc(data, ...)
ntbt_rma(data, ...)

Arguments

data	data frame, tibble, list, ...
...	Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

## Not run: 
library(intubate)
library(magrittr)
library(metafor)


## ntbt_escalc: Calculate Effect Sizes and Outcome Measures
data(dat.bcg)
dat.long <- to.long(measure = "RR", ai = tpos, bi = tneg, ci = cpos, di = cneg,
                    data = dat.bcg, append = FALSE, vlong = TRUE)

## Original function to interface
dat <- escalc(measure="RR", outcome ~ group | study, weights = freq, data = dat.long)
rma(yi, vi, data = dat)

## The interface puts data as first parameter
dat <- ntbt_escalc(dat.long, measure="RR", outcome ~ group | study, weights = freq)
ntbt_rma(dat, yi, vi)

## so it can be used easily in a pipeline.
dat.long %>%
  ntbt_escalc(measure="RR", outcome ~ group | study, weights = freq) %>%
  ntbt_rma(yi, vi)

## End(Not run)

Example output

Loading required package: Matrix
Loading 'metafor' package (version 2.0-0). For an overview 
and introduction to the package please type: help(metafor).

Random-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of total heterogeneity): 0.3132 (SE = 0.1664)
tau (square root of estimated tau^2 value):      0.5597
I^2 (total heterogeneity / total variability):   92.22%
H^2 (total variability / sampling variability):  12.86

Test for Heterogeneity: 
Q(df = 12) = 152.2330, p-val < .0001

Model Results:

estimate      se     zval    pval    ci.lb    ci.ub     
 -0.7145  0.1798  -3.9744  <.0001  -1.0669  -0.3622  ***

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 


Random-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of total heterogeneity): 0.3132 (SE = 0.1664)
tau (square root of estimated tau^2 value):      0.5597
I^2 (total heterogeneity / total variability):   92.22%
H^2 (total variability / sampling variability):  12.86

Test for Heterogeneity: 
Q(df = 12) = 152.2330, p-val < .0001

Model Results:

estimate      se     zval    pval    ci.lb    ci.ub     
 -0.7145  0.1798  -3.9744  <.0001  -1.0669  -0.3622  ***

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 


Random-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of total heterogeneity): 0.3132 (SE = 0.1664)
tau (square root of estimated tau^2 value):      0.5597
I^2 (total heterogeneity / total variability):   92.22%
H^2 (total variability / sampling variability):  12.86

Test for Heterogeneity: 
Q(df = 12) = 152.2330, p-val < .0001

Model Results:

estimate      se     zval    pval    ci.lb    ci.ub     
 -0.7145  0.1798  -3.9744  <.0001  -1.0669  -0.3622  ***

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

intubate documentation built on May 2, 2019, 2:46 p.m.