liSim: Simulate user tracked menstrual cycle data for an individual...

In skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking

Simulate user tracked menstrual cycle data for an individual using the li model.

Description

This function generates synthetic data for user tracked menstrual cycles for a single individual using the li model. For this model Beta0 = log(30), and Gamma0 doesn't really make sense.

Usage

liSim(i, skipProb, maxCycles, trueBetas, trueGammas = NULL, avgCyclesPer)

Arguments

i	Individual identifier. Character, numeric or integer.
skipProb	Vector, ignored for this model.
maxCycles	Integer, Maximum possible number of true cycles per tracked cycle.
trueBetas	Optional. True values for generated mean regression coefficients.
trueGammas	NULL, left for consistency. Will throw error if specified.
avgCyclesPer	Average number of cycles contributed by each individual. Actual number is drawn from Poisson for each person. Default is 7.

Value

'Individual'

Individual identifiers.

'TrackedCycles'

Tracked cycles.

'NumTrue'

Number of true values.

'SkipProb'

Individual's probability of skipping tracking a cycle

'Mean'

Individual's mean values.

'Beta0'

Beta0 true value.

'Gamma0

NA

'Z0'

1

'X0',...,'XN'

Covariate matrix for Mean, where N is the length of trueBetas.

See Also

skipTrack.simulate

skipTrack documentation built on April 3, 2025, 6:21 p.m.