mixSim: 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 mixture model.

Description

This function generates synthetic data for user tracked menstrual cycles for a single individual using the mixture model. For this model Beta_0 is set to log(30) and Gamma_0 is set to 15, although for the skipTrack model this lacks interpretation.

Usage

mixSim(i, skipProb, maxCycles, trueBetas, trueGammas, overlap, avgCyclesPer)

Arguments

i	Individual identifier. Character, numeric, or integer.
skipProb	Vector of probabilities for the number of true cycles per tracked cycle. For example, (.7, .2, .1) means that 70% of observed cycles will contain one true cycle, 20% will contain 2 true cycles, and 10% will contain 3 true cycles.
maxCycles	Maximum number of true cycles per tracked cycle.
trueBetas	Optional. True values for generated mean regression coefficients.
trueGammas	Optional. True values for the generated precision regression coefficients.
overlap	Optional. Number of (non-intercept) columns shared between X and Z. Columns are shared from left to right.
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.

'Mean'

Individual's mean values.

'Beta0'

Beta0 true value.

'Gamma0'

Gamma0 true value.

'X0',...,'XN'

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

'Z0',...,'ZM'

Covariate matrix for precision, where M is the length of trueGammas.

See Also

skipTrack.simulate

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