el_core_eta_state

Computes the capped linear predictor, response probabilities, derivatives,
and stable scores with respect to the linear predictor for a given family.
This helper centralizes the numerically delicate pieces (capping, clipping,
Mills ratios, and score derivatives) and is used consistently across the
EL equation system and analytical Jacobians for both IID and survey designs.

internal

Methods to estimate finite-population parameters under nonresponse that is not missing at
random (NMAR, nonignorable). Incorporates auxiliary information and user-specified response models,
and supports independent samples and complex survey designs via objects from the 'survey' package.
Provides diagnostics and optional variance estimates. For methodological background see
Qin, Leung and Shao (2002) <doi:10.1198/016214502753479338> and Riddles, Kim and Im (2016) <doi:10.1093/jssam/smv047>.

Maciej Ber<c4><99>sewicz

NMAR

Estimation under not Missing at Random Nonresponse

Maciej Beresewicz

Igor Kołodziej

Mateusz Iwaniuk

el_core_eta_state function

<dl><dt>family</dt>
<dd>List-like response family bundle (see <code>logit_family()</code> and
<code>probit_family()</code>).</dd>
<dt>eta_raw</dt>
<dd>Numeric vector of unconstrained linear predictors.</dd>
<dt>eta_cap</dt>
<dd>Scalar cap applied symmetrically to <code>eta_raw</code>.</dd></dl>

Arguments

Core eta-state computation for EL engines — el_core_eta_state

<dl>

<dt>family</dt>
<dd>List-like response family bundle (see <code>logit_family()</code> and
<code>probit_family()</code>).</dd>


<dt>eta_raw</dt>
<dd>Numeric vector of unconstrained linear predictors.</dd>


<dt>eta_cap</dt>
<dd>Scalar cap applied symmetrically to <code>eta_raw</code>.</dd>

</dl>

el_core_eta_state: Core eta-state computation for EL engines

Description

Usage

Value

Arguments