nonverbal_cov

A dataset containing predictors of nonverbal communication of 10 patient-therapist couples.

datasets

An implementation of the multilevel (also known as mixed or random
effects) hidden Markov model using Bayesian estimation in R. The multilevel
hidden Markov model (HMM) is a generalization of the well-known hidden
Markov model, for the latter see Rabiner (1989) <doi:10.1109/5.18626>. The
multilevel HMM is tailored to accommodate (intense) longitudinal data of
multiple individuals simultaneously, see e.g., de Haan-Rietdijk et al.
<doi:10.1080/00273171.2017.1370364>. Using a multilevel framework, we allow
for heterogeneity in the model parameters (transition probability matrix and
conditional distribution), while estimating one overall HMM. The model can
be fitted on multivariate data with either a categorical, normal, or Poisson
distribution, and include individual level covariates (allowing for e.g.,
group comparisons on model parameters). Parameters are estimated using
Bayesian estimation utilizing the forward-backward recursion within a hybrid
Metropolis within Gibbs sampler. Missing data (NA) in the dependent
variables is accommodated assuming MAR. The package also includes various
visualization options, a function to simulate data, and a function to obtain
the most likely hidden state sequence for each individual using the Viterbi
algorithm.

Emmeke Aarts

mHMMbayes

Multilevel Hidden Markov Models Using Bayesian Estimation

Sebastian Mildiner Moraga

nonverbal_cov function

A matrix with 10 rows and 3 variables:<dl>
<dt>diagnosis</dt>
<dd>Diagnosis of the patient, consisting of 0 = depression, 1 = anxiety</dd><dt>std_CDI_change</dt>
<dd>Change in measure for depression (CDI) before and after therapy, standardized scale</dd><dt>std_SCA_change</dt>
<dd>Change in measure for anxiety (SCARED) before and after therapy, standardized scale</dd>
</dl>

Format

Predictors of nonverbal communication — nonverbal_cov

A matrix with 10 rows and 3 variables:<dl>
<dt>diagnosis</dt>
<dd>Diagnosis of the patient, consisting of 0 = depression, 1 = anxiety</dd>

<dt>std_CDI_change</dt>
<dd>Change in measure for depression (CDI) before and after therapy, standardized scale</dd>

<dt>std_SCA_change</dt>
<dd>Change in measure for anxiety (SCARED) before and after therapy, standardized scale</dd>


</dl>

nonverbal_cov: Predictors of nonverbal communication

Description

Usage

Arguments

Format