mmir_model

mmir_model() is a function for the 'mmirestriktor' package that fits
a model to data using one of the specified engines ('lm', 'glm', or 'rlm').
It also provides an option to standardize numeric variables.

Offering enhanced statistical power compared to traditional
hypothesis testing methods, informative hypothesis testing allows researchers
to explicitly model their expectations regarding the relationships among
parameters. An important software tool for this framework is 'restriktor'.
The 'mmirestriktor' package provides 'shiny' web applications to implement
some of the basic functionality of 'restriktor'. The mmirestriktor() function
launches a 'shiny' application for fitting and analyzing models with
constraints. The FbarCards() function launches a card game application which
can help build intuition about informative hypothesis testing. The
iht_interpreter() helps interpret informative hypothesis testing results based
on guidelines in Vanbrabant and Rosseel (2020) <doi:10.4324/9780429273872-14>.

Mackson Ncube

mmirestriktor

Informative Hypothesis Testing Web Applications

mightymetrika, LLC 

mmir_model function

<dl><dt>formula</dt>
<dd>An object of class 'formula' (or one that can be coerced to
that class): a symbolic description of the model to be fitted.</dd>
<dt>data</dt>
<dd>A data frame containing the variables in the model.</dd>
<dt>engine</dt>
<dd>A character string indicating which engine to use for model
fitting. Can be one of 'lm', 'glm', or 'rlm'. Default is 'lm'.</dd>
<dt>standardize</dt>
<dd>Logical. If TRUE, numeric predictor variables in 'data' are
standardized before fitting the model. Default is TRUE.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to the model fitting function
(lm, glm, or rlm).</dd></dl>

Arguments

Fit Restriktor Supported Model — mmir_model

<dl>

<dt>formula</dt>
<dd>An object of class 'formula' (or one that can be coerced to
that class): a symbolic description of the model to be fitted.</dd>


<dt>data</dt>
<dd>A data frame containing the variables in the model.</dd>


<dt>engine</dt>
<dd>A character string indicating which engine to use for model
fitting. Can be one of 'lm', 'glm', or 'rlm'. Default is 'lm'.</dd>


<dt>standardize</dt>
<dd>Logical. If TRUE, numeric predictor variables in 'data' are
standardized before fitting the model. Default is TRUE.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to the model fitting function
(lm, glm, or rlm).</dd>

</dl>

mmir_model: Fit Restriktor Supported Model

Description

Usage

Value

Arguments

Details

See Also

Examples