Computes the interaction effect between Factors A and B in factorial experiments on the coefficient of variation ratio.
Usage
lnCVR_inter(
data,
col_names = c("yi", "vi"),
append = TRUE,
Ctrl_mean,
Ctrl_sd,
Ctrl_n,
A_mean,
A_sd,
A_n,
B_mean,
B_sd,
B_n,
AB_mean,
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_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
- B_mean
Mean outcome from the B treatment
- B_sd
Standard deviation from the B treatment
- B_n
Sample size from the B treatment
- AB_mean
Mean outcome from the interaction AxB 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
# Interaction effect logCVR (Light x Nutrients)
data <- data.frame(
study_id = 1:2,
control_mean = c(7.3, 8.9),
control_sd = c(1.4, 1.7),
control_n = c(20, 18),
light_mean = c(12.8, 14.2),
light_sd = c(3.1, 3.5),
light_n = c(19, 20),
nutrients_mean = c(9.6, 11.1),
nutrients_sd = c(1.9, 2.2),
nutrients_n = c(21, 17),
light_nutrients_mean = c(18.4, 20.7),
light_nutrients_sd = c(4.8, 5.3),
light_nutrients_n = c(18, 19)
)
result <- lnCVR_inter(
data = data,
Ctrl_mean = "control_mean",
Ctrl_sd = "control_sd",
Ctrl_n = "control_n",
A_mean = "light_mean",
A_sd = "light_sd",
A_n = "light_n",
B_mean = "nutrients_mean",
B_sd = "nutrients_sd",
B_n = "nutrients_n",
AB_mean = "light_nutrients_mean",
AB_sd = "light_nutrients_sd",
AB_n = "light_nutrients_n"
)