replicate.cor.gen: Compares and combines any type of correlation in original and...

In dgbonett/vcmeta: Varying Coefficient Meta-Analysis

Compares and combines any type of correlation in original and follow-up studies

Description

This function can be used to compare and combine any type of correlation from an original study and a follow-up study. The confidence level for the difference is 1 – 2*alpha, which is recommended for equivalence testing.

Usage

replicate.cor.gen(alpha, cor1, se1, cor2, se2)

Arguments

alpha	alpha level for 1-alpha confidence
cor1	estimated correlation in original study
se1	standard error of correlation in original study
cor2	estimated correlation in follow-up study
se2	standard error of correlation in follow-up study

Value

A 4-row matrix. The rows are:

• Row 1 summarizes the original study

• Row 2 summarizes the follow-up study

• Row 3 estimates the difference in correlations

• Row 4 estimates the average correlation

The columns are:

• Estimate - correlation estimate (single study, difference, average)

• SE - standard error

• z - z-value

• p - p-value

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

References

\insertRef

Bonett2021vcmeta

Examples

replicate.cor.gen(.05, .454, .170, .318, .098)

# Should return:
#                       Estimate         SE         z            p          LL        UL
# Original:                0.454 0.17000000 2.2869806 0.0221969560  0.06991214 0.7208577
# Follow-up:               0.318 0.09800000 3.0215123 0.0025151541  0.11522137 0.4953353
# Original - Follow-up:    0.136 0.19622436 0.6671281 0.5046902807 -0.21543667 0.4237240
# Average:                 0.386 0.09811218 3.4089419 0.0006521538  0.19606750 0.5480170

dgbonett/vcmeta documentation built on July 12, 2024, 3:12 p.m.