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crov (version 0.3.0)

monoTestBonf: 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)

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.

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).

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

Run this code
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))

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