minter (version 0.1.0)

lnCVR_ind: Individual Effect: Log Coefficient Of Variation Ratio

Description

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
)

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.

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

Author

Facundo Decunta - [e-mail]

Details

See the package vignette for a detailed description of the formula.

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"
)