poLCAParallel.se

Calculates the standard errors and adds them, as attributes, to a fitted
poLCA model object <code>$P.se</code>, <code>$probs.se</code>, <code>$coeff.se</code> and <code>$coeff.V</code>

A 'C++' reimplementation of 'poLCA' - latent class analysis and
latent class regression models for polytomous outcome variables, also known
as latent structure analysis. It attempts to reproduce results and be as
similar as possible to the original code, while running faster, especially
with multiple repetitions, by utilising multiple threads. Further reading is
available on the Queen Mary, University of London, IT Services Research blog
<https://blog.hpc.qmul.ac.uk/speeding_up_r_packages/>.

Sherman Lo

poLCAParallel

Polytomous Variable Latent Class Analysis Parallel

Drew Linzer

Jeffrey Lewis.

poLCAParallel.se function

<dl><dt>polca</dt>
<dd>A model object estimated using the <code>poLCA</code> function</dd>
<dt>is_smooth</dt>
<dd>Logical, experimental, for calculating the standard errors,
whether to smooth the outcome probabilities to produce more numerical stable
results at the cost of bias.</dd></dl>

Arguments

Calculates the standard errors and adds them to a fitted poLCA model object — poLCAParallel.se

<dl>

<dt>polca</dt>
<dd>A model object estimated using the <code>poLCA</code> function</dd>


<dt>is_smooth</dt>
<dd>Logical, experimental, for calculating the standard errors,
whether to smooth the outcome probabilities to produce more numerical stable
results at the cost of bias.</dd>

</dl>

poLCAParallel.se: Calculates the standard errors and adds them to a fitted poLCA model object

Description

Usage

Value

Arguments

Details