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Baylor Electronically Accessible Research Data
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Baylor Electronically Accessible Research Data (BEARdata) is the data repository for Baylor University hosted at the Texas Data Repository
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Mar 25, 2019 - Mixture Modeling with Categorial Responses
Padgett, R. Noah;Tipton, Rebecca J., 2019, "Monte Carlo Simulation Results Categorical Latent Class Analysis",, Texas Data Repository Dataverse, V2
This text (.txt, tab delimited) file contains the extracted results from a Monte Carlo simulation experiment investigating model selection in latent class analysis with categorical indicators.
Plain Text - 6.8 KB - MD5: 6d2454837de5d815702019b352723eeb
Plain Text - 452 B - MD5: ef2208bb426177194d59543bde39de13
Plain Text - 430 B - MD5: 87cd28f976312ad4b1338e06050d3cce
R Syntax - 6.6 KB - MD5: 6777e89e61814a83058c197be8a48d1b
R Syntax - 7.5 KB - MD5: 52b33746def9686ac1b736447380499e
Code for generating tables and figure
Mar 7, 2019 - Glass Box Dataverse
Matthews, Lorin, 2019, "Replication Data for: Mapping the Plasma Potential in a Glass Box",, Texas Data Repository Dataverse, V1
Numerical simulation for electric field inside a glass box
Unknown - 22.7 KB - MD5: 2f748e79b4a8b9544daf9e45959fb372
application/x-xfig - 195.5 KB - MD5: 0979091271b72040a7b4db5feddbf8d6
application/x-xfig - 292.4 KB - MD5: 47528b6ee6a3038883401bfb0cede025
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