monoTestBonf: Monotonicity test

In crov: Constrained Regression Model for an Ordinal Response and Ordinal Predictors

Monotonicity test

Description

Tests the null hypothesis of monotonicity over a set of parameters associated to an ordinal predictor, according to Espinosa and Hennig (2019) <DOI:10.1007/s11222-018-9842-2>.

Usage

monoTestBonf(simultAlpha = 0.05, OP_UMLE, OP_SE)

Arguments

simultAlpha	Numerical value for the simultaneous significance level.
OP_UMLE	Vector with the unconstrained parameter estimates of an ordinal predictor's categories represented by dummy variables in an unconstrained model for ordinal response (see vlgm).
OP_SE	Vector with the standard error of the parameters of an ordinal predictor's categories represented by dummy variables in an unconstrained model for ordinal response (see vlgm).

Value

testRes: String value with outcomes either "Reject H_0" or "Not Reject H_0".

simultAlpha: Numerical value with the simultaneous significance level.

indivAlphaA: Numerical value with the individual significance level for each confidence interval.

simultPvalue: Numerical value with the p-value associated to the simultaneous significance level.

References

Espinosa, J., and Hennig, C. "A constrained regression model for an ordinal response with ordinal predictors." Statistics and Computing 29.5 (2019): 869-890. https://doi.org/10.1007/s11222-018-9842-2.

See Also

mdcp, monoTestConfReg, plotCMLE, vlgm.

Examples

monoTestBonf(simultAlpha=0.05, OP_UMLE = c(-0.352177095,-0.403928770,
-0.290875028,-0.769834449), OP_SE = c(0.246638339,0.247723681,0.267577633,0.300951441))

crov documentation built on Aug. 25, 2023, 5:15 p.m.