# qcapower: 'qcapower' returns a power estimate with regard to the... In qcapower: Estimate Power and Required Sample Size in QCA

## 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

 ``` 1 2 3 4 5 6 7 8 9 10``` ```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.

`qp_quant_plot` and `qp_run_plot`

## Examples

 ```1 2``` ```power_data <- qcapower(cases = 20, null_hypo = 0.8, alt_hypo = 0.95, sims = 10, perms = 1000) head(power_data) ```

qcapower documentation built on March 2, 2020, 5:09 p.m.