STR: Studentized residuals by leave-one-out analysis
In boutliers: Outlier Detection and Influence Diagnostics for Meta-Analysis

STR	R Documentation

Studentized residuals by leave-one-out analysis

Description

Calculating the studentized residuals by leave-one-out analysis (studentized deleted residuals) and the percentiles of their bootstrap distributions.

Usage

STR(y, v, method="REML", data, B=2000, alpha=0.95, seed=123456)

Arguments

`y`	A vector of the outcome measure estimates (e.g., MD, SMD, log OR, log RR, RD)
`v`	A vector of the variance estimate of `y`
`method`	A logical value specifying the estimation method (default: `REML`). The same options as those available for the `method` argument of the `rma` function in the `metafor` package can be used (e.g., `FE` for the fixed-effect model, `SJ` for the Sidik–Jonkman method, and `PM` for the Paule–Mandel method).
`data`	An optional data frame containing the variables `y` and `v`.
`B`	The number of bootstrap resampling (default: 2000)
`alpha`	The bootstrap percentiles to be outputted; 0.5(1-alpha)th and (1-0.5(1-alpha))th pecentiles. Default is 0.95; 2.5th and 97.5th percentiles are calculated.
`seed`	A numeric value that determines the random seed for reproducibility (default: 123456).

Value

The studentized residuals by leave-one-out analysis. The outputs are ordered by the sizes of the studentized residuals.

id: ID of the study.
psi: The studentized residuals by leave-one-out analysis (studentized deleted residuals).
Q1: 0.5(1-alpha)th percentile for the bootstrap distribution of the studentized residual (default: 2.5th percentile).
Q2: 1-0.5(1-alpha)th percentile for the bootstrap distribution of the studentized residual (default: 97.5th percentile).

Examples

require(metafor)
data(PPI)

edat1 <- escalc(ai=d1,n1i=n1,ci=d2,n2i=n2,measure="OR",data=PPI)

STR(yi, vi, data=edat1, B=10)
# Random-effects model (REML estimation).
# This is an example command for illustration. B should be >= 1000.

STR(yi, vi, data=edat1, method="SJ",B=10)
# Random-effects model (Sidik–Jonkman method).
# This is an example command for illustration. B should be >= 1000.

STR(yi, vi, data=edat1, method="FE",B=10)
# Fixed-effects model.
# This is an example command for illustration. B should be >= 1000.

boutliers documentation built on Nov. 26, 2025, 9:06 a.m.