qratio.msm {msm}R Documentation

Estimated ratio of transition intensities

Description

Compute the estimate and approximate standard error of the ratio of two estimated transition intensities from a fitted multi-state model at a given set of covariate values.

Usage

qratio.msm(x, ind1, ind2, covariates = "mean")

Arguments

x A fitted multi-state model, as returned by msm
ind1 Pair of numbers giving the indices in the intensity matrix of the numerator of the ratio, for example, c(1,2).
ind2 Pair of numbers giving the indices in the intensity matrix of the denominator of the ratio, for example, c(2,1).
covariates The covariate values at which to estimate the intensities. This can either be:

the string "mean", denoting the means of the covariates in the data (this is the default),

the number 0, indicating that all the covariates should be set to zero,

or a list of values, with optional names. For example
list (60, 1)
where the order of the list follows the order of the covariates originally given in the model formula, or a named list,
list (age = 60, sex = 1)

Details

For example, we might want to compute the ratio of the progression rate and recovery rate for a fitted model disease.msm with a health state (state 1) and a disease state (state 2). In this case, the progression rate is the (1,2) entry of the intensity matrix, and the recovery rate is the (2,1) entry. Thus to compute this ratio with covariates set to their means, we call

qratio.msm(disease.msm, c(1,2), c(2,1)) .

Standard errors are estimated by the delta method.

Value

A list with components estimate and se, containing the estimate and standard error respectively of the ratio of intensities.

Author(s)

C. H. Jackson chris.jackson@imperial.ac.uk

See Also

qmatrix.msm


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