A Collection of Functions for Negligible Effect/Equivalence Testing

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Documentation for package ‘negligible’ version 0.1.0

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available Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model
data Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model
equiv.reg Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model
is Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model
neg.cat Equivalence Testing for Categorical Variables
neg.cor Test for Lack of Association between Two Continuous Normally Distributed Variables: Equivalence-based correlation tests
neg.esm Test for Evaluating Substantial Mediation
neg.indvars Negligible Effect Test for Variances of Independent Populations
neg.pd Proportional Distance Function (post hoc function - not to be used independently)
neg.reg Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model
neg.twocors Test for Evaluating Negligible Effects of Two Independent or Dependent Correlation Coefficients: Based on Counsell & Cribbie (2015)
neg.twoindmeans Negligible Effect Test on the Difference between the Means of Independent Populations
perfectionism Perfectionism Data
print.neg.cat Equivalence Testing for Categorical Variables
print.neg.cor Test for Lack of Association between Two Continuous Normally Distributed Variables: Equivalence-based correlation tests
print.neg.esm Test for Evaluating Substantial Mediation
print.neg.indvars Negligible Effect Test for Variances of Independent Populations
print.neg.reg Test for Evaluating Negligible Effects of Two Independent or Dependent Correlation Coefficients: Based on Counsell & Cribbie (2015)
print.neg.twocors Test for Evaluating Negligible Effects of Two Independent or Dependent Correlation Coefficients: Based on Counsell & Cribbie (2015)
print.neg.twoindmeans Negligible Effect Test on the Difference between the Means of Independent Populations
When Test for Evaluating Negligible Effects Between a Predictor and Outcome in a Multiple Regression Model