qcapower (version 0.1.0)

qcapower: qcapower returns a power estimate with regard to the consistency of a term, given information about the required parameters

Description

qcapower allows you to estimate power for a term. Probability is the probability of rejecting the null hypothesis that no set relation is in plaace when it is in place, in fact. A term can be a single condition, a conjunction, or a disjunction of any combination of the two.

Usage

qcapower(
  cases,
  null_hypo,
  alt_hypo,
  sims = 1000,
  perms = 10000,
  alpha = 0.05,
  cons_threshold = 0.01,
  set_seed = 135
)

Arguments

cases

Number of cases. In fuzzy-set QCA, equal to total number of cases in the analysis

null_hypo

Null hypothesis (H0). Consistency value separating consistent from inconsistent terms. It is the highest possible consistency value that would let you conclude that no set relation is given.

alt_hypo

Alternative hypothesis (H1). Expected, actual consistency value of term.

sims

Number of simulations for calculating power

perms

Number of permutations of hypothetical dataset per simulation run

alpha

Level of alpha at which statistical significance of H0 is tested

cons_threshold

Degree of tolerance in generating hypothetical data with consistency equaling alt_hypo (see vignette)

set_seed

Parameter for achieving reproducibility of estimate

Value

A dataframe with rows equaling the number of sims. power is the power estimate and is identical for each rows. powercum is the running power estimate up to this row. quant is the 5%-quantile of the permuted distributions. See the vignette for more information.

See Also

qp_quant_plot and qp_run_plot

Examples

# NOT RUN {
power_data <- qcapower(cases = 20, null_hypo = 0.8, alt_hypo = 0.95, sims = 10, perms = 1000)
head(power_data)
# }