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    Multilevel IRT Modeling in Practice with the Package mlirt

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    Variance component models are generally accepted for the analysis of hierarchical structured data. A shortcoming is that outcome variables are still treated as measured without an error. Unreliable variables produce biases in the estimates of the other model parameters. The variability of the relationships across groups and the group-effects on individuals' outcomes differ substantially when taking the measurement error in the dependent variable of the model into account. The multilevel model can be extended to handle measurement error using an item response theory (IRT) model, leading to a multilevel IRT model. This extended multilevel model is in particular suitable for the analysis of educational response data where students are nested in schools and schools are nested within cities/countries.\u

    Multilevel IRT Modeling in Practice with the Package mlirt

    Get PDF
    Variance component models are generally accepted for the analysis of hierarchical structured data. A shortcoming is that outcome variables are still treated as measured without an error. Unreliable variables produce biases in the estimates of the other model parameters. The variability of the relationships across groups and the group-effects on individuals' outcomes differ substantially when taking the measurement error in the dependent variable of the model into account. The multilevel model can be extended to handle measurement error using an item response theory (IRT) model, leading to a multilevel IRT model. This extended multilevel model is in particular suitable for the analysis of educational response data where students are nested in schools and schools are nested within cities/countries.

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    A health needs assessment of offenders on probation caseloads in Nottinghamshire and Derbyshire - report of a pilot study

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    This study was commissioned by the Care Services Improvement Partnership (CSIP) in the East Midlands to investigate the health needs of a sample group offenders managed by The Nottinghamshire and Derbyshire Probation Services
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