Description Usage Arguments Details Value References Examples
View source: R/critical_effect_size_additive.R
The critical effect size for a given experimental design (i.e., number of replicates per treatment).
1 2 3 4 5 6 7 8 | critical_effect_size_additive(
Control_N,
StressorA_N,
StressorB_N,
StressorsAB_N,
Small_Sample_Correction,
Significance_Level
)
|
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) |
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.
The function returns the critical effect size (for the additive null model; see effect_size_additive
)
for a given experimental design.
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.
1 2 3 4 5 6 7 8 9 10 11 | 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)
|
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