Handling Missing Responses in Psychometrics: Methods and Software
The presence of missing responses in assessment settings is inevitable and may yield biased parameter estimates in psychometric modeling if ignored or handled improperly. Many methods have been proposed to handle missing responses in assessment data that are often dichotomous or polytomous. Their ap...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Psych |
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| Online Access: | https://www.mdpi.com/2624-8611/3/4/43 |
| _version_ | 1827669904820535296 |
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| author | Shenghai Dai |
| author_facet | Shenghai Dai |
| author_sort | Shenghai Dai |
| collection | DOAJ |
| description | The presence of missing responses in assessment settings is inevitable and may yield biased parameter estimates in psychometric modeling if ignored or handled improperly. Many methods have been proposed to handle missing responses in assessment data that are often dichotomous or polytomous. Their applications remain nominal, however, partly due to that (1) there is no sufficient support in the literature for an optimal method; (2) many practitioners and researchers are not familiar with these methods; and (3) these methods are usually not employed by psychometric software and missing responses need to be handled separately. This article introduces and reviews the commonly used missing response handling methods in psychometrics, along with the literature that examines and compares the performance of these methods. Further, the use of the TestDataImputation package in R is introduced and illustrated with an example data set and a simulation study. Corresponding R codes are provided. |
| first_indexed | 2024-03-10T03:13:39Z |
| format | Article |
| id | doaj.art-74ae8eecafde4ec9b64a83d286b9e2b9 |
| institution | Directory Open Access Journal |
| issn | 2624-8611 |
| language | English |
| last_indexed | 2024-03-10T03:13:39Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Psych |
| spelling | doaj.art-74ae8eecafde4ec9b64a83d286b9e2b92023-11-23T10:20:14ZengMDPI AGPsych2624-86112021-11-013467369310.3390/psych3040043Handling Missing Responses in Psychometrics: Methods and SoftwareShenghai Dai0Educational Psychology, Washington State University, Pullman, WA 99164, USAThe presence of missing responses in assessment settings is inevitable and may yield biased parameter estimates in psychometric modeling if ignored or handled improperly. Many methods have been proposed to handle missing responses in assessment data that are often dichotomous or polytomous. Their applications remain nominal, however, partly due to that (1) there is no sufficient support in the literature for an optimal method; (2) many practitioners and researchers are not familiar with these methods; and (3) these methods are usually not employed by psychometric software and missing responses need to be handled separately. This article introduces and reviews the commonly used missing response handling methods in psychometrics, along with the literature that examines and compares the performance of these methods. Further, the use of the TestDataImputation package in R is introduced and illustrated with an example data set and a simulation study. Corresponding R codes are provided.https://www.mdpi.com/2624-8611/3/4/43missing responsesassessment datapsychometricsTestDataImputationR |
| spellingShingle | Shenghai Dai Handling Missing Responses in Psychometrics: Methods and Software Psych missing responses assessment data psychometrics TestDataImputation R |
| title | Handling Missing Responses in Psychometrics: Methods and Software |
| title_full | Handling Missing Responses in Psychometrics: Methods and Software |
| title_fullStr | Handling Missing Responses in Psychometrics: Methods and Software |
| title_full_unstemmed | Handling Missing Responses in Psychometrics: Methods and Software |
| title_short | Handling Missing Responses in Psychometrics: Methods and Software |
| title_sort | handling missing responses in psychometrics methods and software |
| topic | missing responses assessment data psychometrics TestDataImputation R |
| url | https://www.mdpi.com/2624-8611/3/4/43 |
| work_keys_str_mv | AT shenghaidai handlingmissingresponsesinpsychometricsmethodsandsoftware |