calculate_expected_values

Calculate expected values for goodness of fit test

Provides tools to adjust estimates of learning for guessing-related
bias in educational and survey research. Implements standard guessing
correction methods and a sophisticated latent class model that leverages
informative pre-post test transitions to account for guessing behavior.
The package helps researchers obtain more accurate estimates of actual
learning when respondents may guess on closed-ended knowledge items.
For theoretical background and empirical validation, see Cor and Sood (2018)
<https://gsood.com/research/papers/guess.pdf>.

Gaurav Sood

guess

Adjust Estimates of Learning for Guessing

Ken Cor

calculate_expected_values function

<dl><dt>gamma_i</dt>
<dd>item-specific gamma value</dd>
<dt>params</dt>
<dd>estimated parameters for the item</dd>
<dt>total_obs</dt>
<dd>total observations for the item</dd>
<dt>model_type</dt>
<dd>"nodk" or "dk" model</dd></dl>

Arguments

Calculate expected values for goodness of fit test — calculate_expected_values

<dl>

<dt>gamma_i</dt>
<dd>item-specific gamma value</dd>


<dt>params</dt>
<dd>estimated parameters for the item</dd>


<dt>total_obs</dt>
<dd>total observations for the item</dd>


<dt>model_type</dt>
<dd>"nodk" or "dk" model</dd>

</dl>

calculate_expected_values: Calculate expected values for goodness of fit test

Description

Usage

Value

Arguments