Package aides is planned to support users to do additional analysis or graphics. Users can use functions in aides by calling the library with following syntax:
library(aides)
Briefly, aides consists of three tasks as follows:
Disparity: a newly proposed assumption regarding disparities in sample size analysis.
Discordance: a newly proposed assumption regarding discordance in rank of study size analysis.
Sequential analysis: a method to examine the sufficiency of information size.
Users can import their data and do relevant tests or graphics using functions in package aides. The present package consists of four functions listed as follows.
Disparity: TestDisparity()
,
PlotDisparity()
.
Discordance: TestDiscordance()
.
Sequential analysis: DoSA()
.
Step 1. Build or load data.
Step 2. Do disparity test using function
TestDisparity()
.
Optional. Illustrate user-defined disparity plot
using function PlotDisparity()
.
Step 1. Build or load data.
Step 2. Do discordance test using function
TestDiscordance()
.
Step 1. Build or load data.
Step 2. Do sequential analysis using function
DoSA()
.
The following steps and syntax demonstrate how user can carry out discordance test.
STEP 1. Import data (example of the study by Fleiss 1993)
library(meta) data("Fleiss1993bin") <- Fleiss1993bin data
STEP 2. Process data
$n <- data$n.asp + data$n.plac data$se <- sqrt((1 / data$d.asp) - (1 / data$n.asp) + (1 / data$d.plac) - (1 / data$n.plac)) data
STEP 3. Test assumption of discordance in study size
<- TestDiscordance(n = n, output se = se, study = study, data = data)
STEP 4. Illustrate discordance plot
TestDiscordance(n = n, se = se, study = study, data = data, plot = TRUE)
Output:
#> Warning: package 'meta' was built under R version 4.2.3 #> Loading 'meta' package (version 6.2-1). #> Type 'help(meta)' for a brief overview. #> Readers of 'Meta-Analysis with R (Use R!)' should install #> older version of 'meta' package: https://tinyurl.com/dt4y5drs #> #> #> Summary of discordance in ranks test: #> Statistics (Bernoulli exact): 2 #> P-value: 0.423 #> Note: No significant finding in the test of discordance in study size ranks.
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Figure 1. an example of discordance plot