Computes the Log of the Coefficient of Variation Ratio between Factor A and the Control treatment.
Usage
lnCVR_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 its 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 treatment
- A_mean
Mean outcome from the treatment
- A_sd
Standard deviation from the treatment
- A_n
Sample size from the treatment
Value
A data frame containing the effect sizes and their sampling variance.
By default, the columns are named yi (effect size) and vi (sampling variance).
If append = TRUE, the results are appended to the input data; otherwise, only the computed effect size columns are returned.
References
Nakagawa, S., Poulin, R., Mengersen, K., Reinhold, K., Engqvist, L., Lagisz, M., & Senior, A. M. (2015). Meta‐analysis of variation: ecological and evolutionary applications and beyond. Methods in Ecology and Evolution, 6(2), 143-152.
Examples
data <- data.frame(
study_id = 1:3,
control_mean = c(8.5, 12.3, 6.8),
control_sd = c(1.8, 2.9, 1.4),
control_n = c(18, 24, 16),
nutrient_mean = c(11.2, 16.7, 9.3),
nutrient_sd = c(3.1, 4.8, 2.7),
nutrient_n = c(19, 22, 17)
)
result <- lnCVR_ind(
data = data,
Ctrl_mean = "control_mean", Ctrl_sd = "control_sd", Ctrl_n = "control_n",
A_mean = "nutrient_mean", A_sd = "nutrient_sd", A_n = "nutrient_n"
)