odds.msm

Odds ratios are computed by exponentiating the estimated covariate effects
on the logit-misclassification probabilities.

models

Functions for fitting continuous-time Markov and hidden
Markov multi-state models to longitudinal data.  Designed for
processes observed at arbitrary times in continuous time (panel data)
but some other observation schemes are supported. Both Markov
transition rates and the hidden Markov output process can be modelled
in terms of covariates, which may be constant or piecewise-constant
in time.

Christopher Jackson

Multi-State Markov and Hidden Markov Models in Continuous Time

odds.msm function

<dl><dt>x</dt>
<dd>Output from <code>msm</code> representing a fitted multi-state
model.</dd>
<dt>odds.scale</dt>
<dd>Vector with same elements as number of covariates on
misclassification probabilities. Corresponds to the increase in each
covariate used to calculate its odds ratio. Defaults to all 1.</dd>
<dt>cl</dt>
<dd>Width of the symmetric confidence interval to present. Defaults
to 0.95.</dd></dl>

Arguments

C. H. Jackson <a href="/link/chris.jackson%40mrc-bsu.cam.ac.uk?package=msm&version=1.8.1" data-mini-rdoc="msm::chris.jackson@mrc-bsu.cam.ac.uk">chris.jackson@mrc-bsu.cam.ac.uk</a>

Author

Calculate tables of odds ratios for covariates on misclassification
probabilities — odds.msm

<dl>

<dt>x</dt>
<dd>Output from <code>msm</code> representing a fitted multi-state
model.</dd>


<dt>odds.scale</dt>
<dd>Vector with same elements as number of covariates on
misclassification probabilities. Corresponds to the increase in each
covariate used to calculate its odds ratio. Defaults to all 1.</dd>


<dt>cl</dt>
<dd>Width of the symmetric confidence interval to present. Defaults
to 0.95.</dd>

</dl>

C. H. Jackson <a href='mailto:chris.jackson@mrc-bsu.cam.ac.uk'>chris.jackson@mrc-bsu.cam.ac.uk</a>

odds.msm: Calculate tables of odds ratios for covariates on misclassification probabilities

Description

Usage

Value

Arguments

Author

See Also