Using plausible values when fitting multilevel models with large-scale assessment data using R
Abstract The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-03-01
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| Series: | Large-scale Assessments in Education |
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| Online Access: | https://doi.org/10.1186/s40536-024-00192-0 |
| _version_ | 1797266704854679552 |
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| author | Francis L. Huang |
| author_facet | Francis L. Huang |
| author_sort | Francis L. Huang |
| collection | DOAJ |
| description | Abstract The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional functions in R that extend the functionality of the WeMix (Bailey et al., 2023) package to allow for the automatic pooling of plausible values. In addition, functions for model comparisons using plausible values and the ability to export output to different formats (e.g., Word, html) are also provided. |
| first_indexed | 2024-04-25T01:04:56Z |
| format | Article |
| id | doaj.art-7220d9491a544032905af94d737c5822 |
| institution | Directory Open Access Journal |
| issn | 2196-0739 |
| language | English |
| last_indexed | 2024-04-25T01:04:56Z |
| publishDate | 2024-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Large-scale Assessments in Education |
| spelling | doaj.art-7220d9491a544032905af94d737c58222024-03-10T12:18:24ZengSpringerOpenLarge-scale Assessments in Education2196-07392024-03-0112111510.1186/s40536-024-00192-0Using plausible values when fitting multilevel models with large-scale assessment data using RFrancis L. Huang0University of MissouriAbstract The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional functions in R that extend the functionality of the WeMix (Bailey et al., 2023) package to allow for the automatic pooling of plausible values. In addition, functions for model comparisons using plausible values and the ability to export output to different formats (e.g., Word, html) are also provided.https://doi.org/10.1186/s40536-024-00192-0RMultilevel modelsPlausible valuesWeights |
| spellingShingle | Francis L. Huang Using plausible values when fitting multilevel models with large-scale assessment data using R Large-scale Assessments in Education R Multilevel models Plausible values Weights |
| title | Using plausible values when fitting multilevel models with large-scale assessment data using R |
| title_full | Using plausible values when fitting multilevel models with large-scale assessment data using R |
| title_fullStr | Using plausible values when fitting multilevel models with large-scale assessment data using R |
| title_full_unstemmed | Using plausible values when fitting multilevel models with large-scale assessment data using R |
| title_short | Using plausible values when fitting multilevel models with large-scale assessment data using R |
| title_sort | using plausible values when fitting multilevel models with large scale assessment data using r |
| topic | R Multilevel models Plausible values Weights |
| url | https://doi.org/10.1186/s40536-024-00192-0 |
| work_keys_str_mv | AT francislhuang usingplausiblevalueswhenfittingmultilevelmodelswithlargescaleassessmentdatausingr |