minter0.1.0 package

Effect Sizes for Meta-Analysis of Interactions from Factorial Experiments

dot-compute_and_format

Compute And Format

dot-interaction_SMD

Interaction effect: Standardized mean difference

dot-j_correction

Correction for small-sample bias

dot-lnVR_args

Required columns for computing lnVR

dot-main_SMD

Main effect: Standardized Mean Difference

dot-pooled_sd

Pooled Standard Deviation for SMD in factorial experiments

dot-simple_SMD

Simple effect: Standardized Mean Difference

dot-time_interaction_lnCVR

Log Coefficient of Variation Ratio: Interaction Between Experimental T...

dot-time_interaction_lnRR

Log Response Ratio: Interaction Between Experimental Treatment and Tim...

dot-time_interaction_lnVR

Log of Variability Ratio: Interaction Between Experimental Treatment a...

dot-time_interaction_SMD

Standardized Mean Difference for the interaction between Experimental ...

dot-time_pooled_sd

Pooled Standard Deviation for SMD in non-independent factorial

lnCVR_ind

Individual Effect: Log Coefficient Of Variation Ratio

lnCVR_inter

Interaction Effect: Log Coefficient of Variation Ratio

lnCVR_main

Main Effect: Log Coefficient Of Variation Ration

lnRR_ind

Simple effect: Log Response Ratio

lnRR_inter

Interaction effect: Log Response Ratio

lnRR_main

Main effect: Log Response Ratio

lnVR_ind

Individual effect: Log of Variability Ratio

lnVR_inter

Interaction effect: Log Variability Ratio

lnVR_main

Main Effect: Log of the Variability Ratio

SMD_ind

Simple effect: Standardized Mean Difference

SMD_inter

Interaction effect: Standardized mean difference

SMD_main

Main effect: Standardized Mean Difference

time_lnCVR

Log Coefficient of Variation Ratio: Interaction Between Treatment and ...

time_lnRR

Log Response Ratio: Interaction Between Treatment and Time

time_lnVR

Log of Variability Ratio: Interaction Between Treatment and Time

time_SMD

Standardized Mean Difference: Interaction Between Treatment and Time

Compute effect sizes and their sampling variances from factorial experimental designs. The package supports calculation of simple effects, overall effects, and interaction effects for use in factorial meta-analyses. See Gurevitch et al. (2000) <doi:10.1086/303337>, Morris et al. (2007) <doi:10.1890/06-0442>, Lajeunesse (2011) <doi:10.1890/11-0423.1> and Macartney et al. (2022) <doi:10.1016/j.neubiorev.2022.104554>.

  • Maintainer: Facundo Decunta
  • License: MIT + file LICENSE
  • Last published: 2025-10-06