precal_cumulative_order

Performs a cumulative precalibration across multiple probability samples by
sequentially calibrating each sample's weights to align with the marginal
totals of the previous samples. Called internally by <code>est_pw()</code>.

internal

Provides pseudo-weighted estimates of means and
prevalences for finite population inference from nonprobability
samples using auxiliary information from one or multiple probability
reference surveys. The package supports estimation with multiple
reference surveys, allowing auxiliary information to be combined
when no single survey contains all variables relevant to
participation. Optional cumulative precalibration can be applied to
align weighted totals of shared variables across surveys. Methods
are based on the generalized estimating equations framework of
Landsman et al. (2026) <doi:10.1002/sim.70403> for correcting
participation bias. For a single reference survey, the package
implements the raking ratio calibration method and includes the
adjusted logistic propensity (ALP) method of Wang, Valliant, and Li
(2021) <doi:10.1002/sim.9122>, as well as the Chen-Li-Wu (CLW)
method of Chen, Li, and Wu (2020) <doi:10.1080/01621459.2019.1677241>.
Analytic variance estimation uses Taylor linearization and accounts
for complex sampling designs in the reference surveys via integration
with the 'survey' package.

Jiakun Lin

nonprobsampling

Inference for Nonprobability Samples Using Multiple Reference
Surveys

Victoria Landsman

Aya A. Mitani

precal_cumulative_order function

<dl><dt>sp_raw</dt>
<dd>A list of data frames (raw reference samples).</dd>
<dt>sp_new</dt>
<dd>A list of data frames (working reference samples) with the same
structure as <code>sp_raw</code>. Calibrated weights are written back in place.</dd>
<dt>weight</dt>
<dd>A list of weight column name strings, one per sample.</dd>
<dt>sp_order</dt>
<dd><code>"size"</code> to process largest sample first; otherwise
the original list order is used.</dd></dl>

Arguments

Cumulative precalibration across multiple probability samples — precal_cumulative_order

<dl>

<dt>sp_raw</dt>
<dd>A list of data frames (raw reference samples).</dd>


<dt>sp_new</dt>
<dd>A list of data frames (working reference samples) with the same
structure as <code>sp_raw</code>. Calibrated weights are written back in place.</dd>


<dt>weight</dt>
<dd>A list of weight column name strings, one per sample.</dd>


<dt>sp_order</dt>
<dd><code>"size"</code> to process largest sample first; otherwise
the original list order is used.</dd>

</dl>

precal_cumulative_order: Cumulative precalibration across multiple probability samples

Description

Usage

Value

Arguments