p.threshold.adjust

The total number of hypotheses tested, or the number of
configurations utilized by the Quine-McCluskey algorithm in fsQCA (including
logical remainders, if they are used in the analysis).

total.configs

The adjustment method used to calculate p-values (see
<code><a rd-options="" href="/link/p.adjust?package=QCAfalsePositive&version=1.1.1" data-mini-rdoc="QCAfalsePositive::p.adjust">p.adjust</a></code> for details).

my.method


Internal function. Calculates the adjusted thresholds for multiple significance
tests, assuming that the original threshold for a single test is p<0.05. used="" by="" <code=""><a rd-options="" href="/link/fsQCApermTest?package=QCAfalsePositive&version=1.1.1" data-mini-rdoc="QCAfalsePositive::fsQCApermTest">fsQCApermTest</a> to calculate confidence intervals.
</0.05.>

P-value

threshold

fsQCA

Implements tests for Type I error in Qualitative Comparative Analysis (QCA) that take into account the multiple hypothesis tests inherent in the procedure. Tests can be carried out on three variants of QCA: crisp-set QCA (csQCA), multi-value QCA (mvQCA) and fuzzy-set QCA (fsQCA). For fsQCA, the fsQCApermTest() command implements a permutation test that provides 95% confidence intervals for the number of counterexamples and degree of consistency, respectively. The distributions of permuted values can be plotted against the observed values. For csQCA and mvQCA, simple binomial tests are implemented in csQCAbinTest() and mvQCAbinTest(), respectively.

p.threshold.adjust: Calculate Vector of p-value Thresholds for Multiple Inference

Description

Usage

Arguments

Value

Examples