Home

Menu

Loading wiki pages...

View
Wiki Version:
<p>The project contains the code and correlation matrices for the paper <em>What is central to belief system networks?</em></p> <p><strong>This project contains the following files.</strong></p> <h1>Code</h1> <h2>Custom Functions</h2> <ul> <li>NCTmissing.R: code from NetworkComparisonTest, but adjusted to use fiml for missing data</li> <li>tidystatfunctions.R: functions to store data in tidystats format for tests not covered by tidystats</li> </ul> <h2>R code</h2> <ul> <li>master.R: code to run all of the analyses</li> </ul> <h3>Estimate Networks and Centrality with all the available data in each wave</h3> <ul> <li>estimate networks.R</li> <li>estimate centrality defaults.R</li> <li>estimate centrality ranked.R</li> </ul> <h3>Estimate Networks and Centrality with only items available in at least 6 waves</h3> <ul> <li>estimate networks at least 6.R</li> <li>estimate centrality defaults at least 6.R</li> <li>estimate centrality ranked at least 6.R</li> </ul> <h3>Estimate Networks for people high and low in political knowledge for all available data</h3> <ul> <li>political knowledge networks.R</li> <li>political knowledge estimate centrality defaults.R</li> <li>political knowledge estimate centrality ranked.R</li> </ul> <h3>Estimate Networks for people high and low in political knowledge with only items available in at least 6 waves</h3> <ul> <li>political knowledge networks at least 6.R</li> <li>political knowledge estimate centrality defaults at least 6.R</li> <li>political knowledge estimate centrality ranked at least 6.R</li> </ul> <h3>Estimate Networks for people high and low in political knowledge using quartiles (suggested by reviewer)</h3> <ul> <li>political knowledge networks quartiles.R</li> <li>political knowledge quartiles estimate centrality defaults.R</li> </ul> <h3>Estimate Networks for people high and low in education for all available data</h3> <ul> <li>education networks.R</li> <li>education estimate centrality defaults.R</li> <li>education estimate centrality ranked.R</li> </ul> <h3>Estimate Networks for people high and low in education with only items available in at least 6 waves</h3> <ul> <li>education networks at least 6.R</li> <li>education estimate centrality defaults at least 6.R</li> <li>education estimate centrality ranked at least 6.R</li> </ul> <h3>Estimate Networks for voting and behavior</h3> <ul> <li>behavior network.R</li> <li>behavior network at least 6.R</li> </ul> <h3>Estimate education and political knowledge differences for voting (suggested by reviewer)</h3> <ul> <li>behavior network with knowledge.R</li> </ul> <h2>Layout files</h2> <p>Several .rds (r files) are included that specify the layout for the network figures</p> <ul> <li>layout1.rds -&gt; layout7.rds: layout for networks with all available items</li> <li>layout16.rds -&gt; layout76.rds: layout for networks with items from at least 6 waves</li> <li>mx.rds: maximum value for the network graphs</li> </ul> <h2>Bootstrap files</h2> <p>The bootstrapping analyses can take a long time to run. They are completed using the code above. They are then saved into the folder "boots".</p> <p>## Other files</p> <ul> <li>results.csv: Results from statistical tests saved in tidystats format.</li> <li>sessioninfo.txt: information about the computer environment</li> </ul> <h1>Matrices</h1> <h2>Correlation Matrices</h2> <p>Correlation matrices can be used to recreate the network analyses in the paper. Names of matrices and the code used to create them are below.</p> <ul> <li>cor1.rds -&gt; cor7.rds: estimated with "estimate networks.R"</li> <li>cor1.6.rds -&gt; cor7.6.rds: estimated with "estimate networks at least 6.R"</li> <li>cor1.pkhi.rds -&gt; cor7.pkhi.rds: estimated with "political knowledge networks.R"</li> <li>cor1.pklo.rds -&gt; cor7.pklo.rds: estimated with "political knowledge networks.R"</li> <li>cor1.pkhi.6.rds -&gt; cor7.pkhi.6.rds: estimated with "political knowledge networks at least 6.R"</li> <li>cor1.pklo.6.rds -&gt; cor7.pklo.6.rds: estimated with "political knowledge networks at least 6.R"</li> <li>cor1.edhi.rds -&gt; cor7.edhi.rds: estimated with "education networks.R"</li> <li>cor1.edlo.rds -&gt; cor7.edlo.rds: estimated with "education networks.R"</li> <li>cor1.edhi.6.rds -&gt; cor7.edhi.6.rds: estimated with "education networks at least 6.R"</li> <li>cor1.edlo.6.rds -&gt; cor7.edlo.6.rds: estimated with "education networks at least 6.R"</li> <li>cor1.pkloqrt.rds -&gt; cor7.pkloqrt.rds: estimated with "political knowledge networks quartiles.R"</li> <li>cor1.pkhiqrt.rds -&gt; cor7.pkhiqrt.rds: estimated with "political knowledge networks quartiles.R"</li> </ul> <p>## Weights matrices</p> <p>To calculate the networks including behavior the raw data is necessary; a correlation matrix won't do. To help make this reproducible without direct access to the raw data, the weights matrices, used to construct the behavior networks are below.</p> <ul> <li>fit3.beh.rds -&gt; fit4.beh.rds: estimated with "behavior network.R"</li> <li>fit3.beh6.rds -&gt; fit4.beh6.rds: estimated with "behavior network at least 6.R"</li> <li>Remaining fit..rds : estimated with "behavior network with knowledge.R"</li> </ul> <h1>Centrality Data</h1> <p>The centrality data used for the key ANOVAs and figures in the text are saved separately. These files are all "centrality....csv" files. The main results are from "centrality.csv".</p> <h1>Shortest Path data</h1> <p>The shortest path data used for the key ANOVAs and figures in the text are saved separately. These files are all "shorts...csv" files. The main results are from "shorts.beh.csv".</p>
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.