Computes the overral log of the variability ratio for Factor A across levels of Factor B.
Usage
lnVR_main(
data,
col_names = c("yi", "vi"),
append = TRUE,
Ctrl_sd,
Ctrl_n,
A_sd,
A_n,
B_sd,
B_n,
AB_sd,
AB_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_sd
Standard deviation from the control treatment
- Ctrl_n
Sample size from the control treatment
- A_sd
Standard deviation from the A treatment
- A_n
Sample size from the A treatment
- B_sd
Standard deviation from the B treatment
- B_n
Sample size from the B treatment
- AB_sd
Standard deviation from the interaction AxB treatment
- AB_n
Sample size from the interaction AxB 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.
Examples
# Example for main effect in 2x2 factorial focusing on variability (Fire x Grazing)
data <- data.frame(
study_id = 1:2,
control_sd = c(2.0, 2.3), control_n = c(20, 18),
fire_sd = c(2.8, 3.1), fire_n = c(19, 20),
grazing_sd = c(2.2, 2.5), grazing_n = c(21, 17),
fire_grazing_sd = c(3.5, 3.8), fire_grazing_n = c(18, 19)
)
result <- lnVR_main(
data = data,
Ctrl_sd = "control_sd", Ctrl_n = "control_n",
A_sd = "fire_sd", A_n = "fire_n",
B_sd = "grazing_sd", B_n = "grazing_n",
AB_sd = "fire_grazing_sd", AB_n = "fire_grazing_n"
)