| replicate.mean1 {vcmeta} | R Documentation |
Compares and combines single mean in original and follow-up studies
Description
This function computes confidence intervals for a single mean from an original study and a follow-up study. Confidence intervals for the difference between the two means and average of the two means are also computed. Equality of variances across studies is not assumed. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence intervals for the difference and average. The same results can be obtained using the meta.lc.mean1 function with appropriate contrast coefficients. The confidence level for the difference is 1 – 2*alpha, which is recommended for equivalence testing.
Usage
replicate.mean1(alpha, m1, sd1, n1, m2, sd2, n2)
Arguments
alpha |
alpha level for 1-alpha confidence |
m1 |
estimated mean in original study |
sd1 |
estimated SD in original study |
n1 |
sample size in original study |
m2 |
estimated mean in follow-up study |
sd2 |
estimated SD in follow-up study |
n2 |
sample size for 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 means
Row 4 estimates the average mean
The columns are:
Estimate - mean estimate (single study, difference, average)
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
df - degrees of freedom
References
Bonett DG (2021). “Design and analysis of replication studies.” Organizational Research Methods, 24(3), 513–529. ISSN 1094-4281, doi:10.1177/1094428120911088.
Examples
replicate.mean1(.05, 21.9, 3.82, 40, 25.2, 3.98, 75)
# Should return:
# Estimate SE LL UL df
# Original: 21.90 0.6039950 20.678305 23.121695 39.00000
# Follow-up: 25.20 0.4595708 24.284285 26.115715 74.00000
# Original - Follow-up: -3.30 0.7589567 -4.562527 -2.037473 82.63282
# Average: 23.55 0.3794784 22.795183 24.304817 82.63282