critical_effect_size_additive {multiplestressR}

Critical Effect Sizes (for the additive null model)

Description

The critical effect size for a given experimental design (i.e., number of replicates per treatment).

Usage

critical_effect_size_additive(
  Control_N,
  StressorA_N,
  StressorB_N,
  StressorsAB_N,
  Small_Sample_Correction,
  Significance_Level
)

Arguments

Control_N

Sample size of the control treatment (numeric)

StressorA_N

Sample size of stressor A treatment (numeric)

StressorB_N

Sample size of stressor B treatment (numeric)

StressorsAB_N

Sample size of stressors A and B treatment (numeric)

Small_Sample_Correction

Whether the correction for small sample sizes should be enacted (TRUE or FALSE; default is TRUE)

Significance_Level

The value of alpha for which confidence intervals are calculated (numeric, between 0 and 1; default is 0.05)

Details

The critical effect size represents the minimum effect size required for a significant result to be returned (see Burgess et al. (2021)).

For the additive null model, the critical effect size is directly related to treatment sample sizes.

Value

The function returns the critical effect size (for the additive null model; see effect_size_additive) for a given experimental design.

References

Burgess, B. J., Jackson, M. C., & Murrell, D. J. (2021). Multiple stressor null models frequently fail to detect most interactions due to low statistical power. bioRxiv.

Examples

critical_effect_size_additive(Control_N     = 4,
                             StressorA_N   = 4,
                             StressorB_N   = 4,
                             StressorsAB_N = 4)

critical_effect_size_additive(Control_N     = 3,
                             StressorA_N   = 3,
                             StressorB_N   = 3,
                             StressorsAB_N = 3,
                             Small_Sample_Correction = FALSE,
                             Significance_Level = 0.10)