NuModelTest_cont

Null Model Test and post-hoc Test in longdat_cont() pipeline

This tool takes longitudinal dataset as input and analyzes if there is significant
change of the features over time (a proxy for treatments), while detects and controls
for 'covariates' simultaneously. 'LongDat' is able to take in several data types as input,
including count, proportion, binary, ordinal and continuous data. The output table contains
p values, effect sizes and 'covariates' of each feature, making the downstream analysis easy.

Chia-Yu Chen

LongDat

A Tool for 'Covariate'-Sensitive Longitudinal Analysis on
'omics' Data

Sofia Forslund

NuModelTest_cont function

<dl><dt>N</dt>
<dd>Internal function argument.</dd>
<dt>data_type</dt>
<dd>Internal function argument.</dd>
<dt>test_var</dt>
<dd>Internal function argument.</dd>
<dt>melt_data</dt>
<dd>Internal function argument.</dd>
<dt>variables</dt>
<dd>Internal function argument.</dd>
<dt>verbose</dt>
<dd>Internal function argument.</dd></dl>

Arguments

Null Model Test and post-hoc Test in longdat_cont() pipeline — NuModelTest_cont

<dl>

<dt>N</dt>
<dd>Internal function argument.</dd>


<dt>data_type</dt>
<dd>Internal function argument.</dd>


<dt>test_var</dt>
<dd>Internal function argument.</dd>


<dt>melt_data</dt>
<dd>Internal function argument.</dd>


<dt>variables</dt>
<dd>Internal function argument.</dd>


<dt>verbose</dt>
<dd>Internal function argument.</dd>

</dl>

NuModelTest_cont: Null Model Test and post-hoc Test in longdat_cont() pipeline

Description

Arguments