Computes the individual or simple effect of Factor A over the Control.
Usage
lnRR_ind(
data,
col_names = c("yi", "vi"),
append = TRUE,
Ctrl_mean,
Ctrl_sd,
Ctrl_n,
A_mean,
A_sd,
A_n
)Arguments
- data
Data frame containing the variables used.
- col_names
Vector of two strings to name the output columns for the effect size and it's sampling variance. Default is 'yi' and 'vi'.
- append
Logical. Append the results to
data. Default is TRUE- Ctrl_mean
Mean outcome from the Control treatment
- Ctrl_sd
Standard deviation from the control treatment
- Ctrl_n
Sample size from the control streatment
- A_mean
Mean outcome from the experimental treatment
- A_sd
Standard deviation from the experimental treatment
- A_n
Sample size from the experimental treatment
Details
It is the classic Log Response Ratio (lnRR), which can also be computed
with metafor's escalc() function using measure = "ROM".
See the package vignette for a detailed description of the formula.
References
Morris, W. F., Hufbauer, R. A., Agrawal, A. A., Bever, J. D., Borowicz, V. A., Gilbert, G. S., ... & Vázquez, D. P. (2007). Direct and interactive effects of enemies and mutualists on plant performance: a meta‐analysis. Ecology, 88(4), 1021-1029. https://doi.org/10.1890/06-0442
Lajeunesse, M. J. (2011). On the meta‐analysis of response ratios for studies with correlated and multi‐group designs. Ecology, 92(11), 2049-2055. https://doi.org/10.1890/11-0423.1