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Reconsidering cluster bias (Isomorphism) in multilevel data: A Monte Carlo comparison of free and constrained baseline approaches

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DataCite Commons2022-02-02 更新2024-07-25 收录
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https://figshare.com/articles/dataset/Detecting_Cluster_Bias_in_Multilevel_Measurement_Models_A_Monte_Carlo_Examination_of_a_New_Free_Baseline_Procedurem/4805611/3
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资源简介:
Fixes problem with previous upload where some folders were incomplete. Adds simulation conditions where referent indicator is biased. Changes free baseline model conditions so that free baseline is always minimally identifiable. Original description: This file contains accompanying materials for this Monte Carlo study on free baseline testing for cluster bias (in review). The cell design and parameters excel file describes the parameters used in each of the cells of the design. The inputs and outputs for generation and analysis are included, along with the summary files that the save data command produces. The python scripts are short pieces of code that will extract the summary parameters and fit statistics from the outputs of each run that the Mplus save data output line generates. Run them from the command line. You can request the line you want according to the listing at the end of the Mplus summary files, the fit statistics turn out to be lines 6 and 7 for fixed baseline and 8 and 9 for free baseline conditions. I am sure others can do this more efficiently, i put it here in case it is of use to anyone. The collated results in excel file contains the summaries of parameters and fit, scroll to the far right of each worksheet to see the summary calculation tables.
提供机构:
figshare
创建时间:
2017-08-04
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