powerADgen

Estimates the statistical power of an affect dynamics time series study for a given sampling, effect size, alpha level and metric of interest.

powerADgen(
  individuals,
  samples,
  metric,
  r,
  p.value = 0.05,
  min,
  max,
  data,
  id,
  affect,
  time,
  perm = 100
)

Arguments

individuals

Number of individuals sampled.

samples

Number of affect observations per individual.

metric

Metric of interest. Must be a single character from "Average", "Rel.SD", "SD", "RMSSD", "TKEO", "PAC" or "Autocorrelation".

r

Number from 0.01 to 0.99 indicating the expected effect size (Pearson correlation) of interest.

p.value

Alpha level. Must be one of the following numbers: 0.01, 0.05, 0.001, 0.005, 0.001. Defaults to 0.05.

min

Affect scale lower bound.

max

Affect scale upper bound.

data

Data frame containing affect observations used perform power analysis.

id

Name of variable containing id observations.

affect

Name of variable containing affect observations.

time

Name of variable containing observation order/time stamp of affect reports.

perm

Number of simulations employed in power analysis. For robust power calculations, we recommend using a minimum of 1000 simulations.

References

Pirla, Taquet and Quoidbach (2021). ADD REFERENCE