ctDiscretiseData

Extends and rounds timing information so equal intervals, according to specified
timestep, are achieved. NA's are inserted in other columns as necessary,
any columns specified by TDpredNames or TIpredNames have zeroes rather than NA's
inserted (because some estimation routines do not tolerate NA's in covariates).

Hierarchical continuous (and discrete) time state space modelling, for linear
and nonlinear systems measured by continuous variables, with limited support for
binary data. The subject specific dynamic system is modelled as a stochastic
differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models.
Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default.
Nonlinearities, (state dependent parameters) and random effects on all parameters
are possible, using either max likelihood / max a posteriori optimization
(with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling.
See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf>
for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian
linear SDE approach,
see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>.
Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> .
Stan based functions are not available on 32 bit Windows systems at present.
<https://cdriver.netlify.app/> contains some tutorial blog posts.

Charles Driver

ctsem

Continuous Time Structural Equation Modelling

Manuel Voelkle

Han Oud

Trustees of Columbia University 

ctDiscretiseData function

<dl><dt>dlong</dt>
<dd>Long format data</dd>
<dt>timestep</dt>
<dd>Positive real value to discretise</dd>
<dt>timecol</dt>
<dd>Name of column containing absolute (not intervals) time information.</dd>
<dt>idcol</dt>
<dd>Name of column containing subject id variable.</dd>
<dt>TDpredNames</dt>
<dd>Vector of column names of any time dependent predictors</dd>
<dt>TIpredNames</dt>
<dd>Vector of column names of any time independent predictors</dd></dl>

Arguments

Discretise long format continuous time (ctsem) data to specific timestep. — ctDiscretiseData

<dl>

<dt>dlong</dt>
<dd>Long format data</dd>


<dt>timestep</dt>
<dd>Positive real value to discretise</dd>


<dt>timecol</dt>
<dd>Name of column containing absolute (not intervals) time information.</dd>


<dt>idcol</dt>
<dd>Name of column containing subject id variable.</dd>


<dt>TDpredNames</dt>
<dd>Vector of column names of any time dependent predictors</dd>


<dt>TIpredNames</dt>
<dd>Vector of column names of any time independent predictors</dd>

</dl>

ctDiscretiseData: Discretise long format continuous time (ctsem) data to specific timestep.

Description

Usage

Value

Arguments

Examples