Multilevel multidimensional item response model with a multilevel latent covariate
In a pre‐test–post‐test cluster randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre‐test scores and other related covariates while estimating an intervention effect at post‐test. In many applications in education, the total post‐test and pre‐t...
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| Veröffentlicht in: | British journal of mathematical & statistical psychology 2015-11, Vol.68 (3), p.410-433 |
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| container_title | British journal of mathematical & statistical psychology |
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| creator | Cho, Sun-Joo Bottge, Brian |
| description | In a pre‐test–post‐test cluster randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre‐test scores and other related covariates while estimating an intervention effect at post‐test. In many applications in education, the total post‐test and pre‐test scores, ignoring measurement error, are used as response variable and covariate, respectively, to estimate the intervention effect. However, these test scores are frequently subject to measurement error, and statistical inferences based on the model ignoring measurement error can yield a biased estimate of the intervention effect. When multiple domains exist in test data, it is sometimes more informative to detect the intervention effect for each domain than for the entire test. This paper presents applications of the multilevel multidimensional item response model with measurement error adjustments in a response variable and a covariate to estimate the intervention effect for each domain. |
| doi_str_mv | 10.1111/bmsp.12051 |
| format | Article |
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| subjects | Algorithms Clinical trials Comparative Analysis Computation Computer Simulation Data Interpretation, Statistical Educational Measurement - methods Error of Measurement Estimation bias Fractions Hierarchical Linear Modeling Intervention Item Response Theory Mathematics Tests measurement error Measurement errors Middle School Students Models, Statistical multidimensional item response model Multifactor Dimensionality Reduction multilevel model Outcome Assessment (Health Care) - methods Pretests Posttests Program Effectiveness Randomized Controlled Trials as Topic Regression Analysis Reproducibility of Results Scores Sensitivity and Specificity Statistical Analysis Statistical inference |
| title | Multilevel multidimensional item response model with a multilevel latent covariate |
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