Sökning: "item response theory"

Visar resultat 6 - 10 av 32 avhandlingar innehållade orden item response theory.

1. 6. Extensions of the kernel method of test score equating

   Författare :Gabriel Wallin; Marie Wiberg; Jenny Häggström; Anton A. Béguin; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Test equating; Nonequivalent groups; Standard error of equating; bandwidth selection; log-linear models; item response theory; Statistics; statistik;

   Sammanfattning : This thesis makes contributions within the area of test score equating and specifically kernel equating. The first paper of this thesis studies the estimation of the test score distributions needed in kernel equating. LÄS MER

3. 7. Observed score equating with covariates

   Författare :Kenny Bränberg; Marie Wiberg; Xavier de Luna; Dag Sörbom; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Equating; observed score equating; true scores; item response theory; linear equating function; equipercentile equating; kernel equating; covariates; linear regression; mean squared error; Statistics; Statistik; Statistics; statistik;

   Sammanfattning : In test score equating the focus is on the problem of finding the relationship between the scales of different test forms. This can be done only if data are collected in such a way that the effect of differences in ability between groups taking different test forms can be separated from the effect of differences in test form difficulty. LÄS MER

4. 8. Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables

   Författare :Myrsini Katsikatsou; Fan Yang-Wallentin; Irini Moustaki; Karl Gustav Jöreskog; Ruggero Bellio; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; latent variable models; factor analysis; structural equation models; Thurstonian model; item response theory; composite likelihood estimation; pairwise likelihood estimation; maximum likelihood; weighted least squares; ordinal variables; ranking variables; lavaan; Statistics; Statistik;

   Sammanfattning : The estimation of latent variable models with ordinal and continuous, or ranking variables is the research focus of this thesis. The existing estimation methods are discussed and a composite likelihood approach is developed. LÄS MER

5. 9. Longitudinal Models for Quantifying Disease and Therapeutic Response in Multiple Sclerosis

   Författare :Ana M. Novakovic; Mats O. Karlsson; Etienne Pigeolet; Uppsala universitet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; nonlinear mixed-effects models; pharmacometrics; NONMEM; multiple sclerosis; cladribine; EDSS; item response theory; relapse rate; absolute lymphocyte count; total volume T2 lesions; burden of disease; power; sample size; Pharmaceutical Science; Farmaceutisk vetenskap;

   Sammanfattning : Treatment of patients with multiple sclerosis (MS) and development of new therapies have been challenging due to the disease complexity and slow progression, and the limited sensitivity of available clinical outcomes. Modeling and simulation has become an increasingly important component in drug development and in post-marketing optimization of use of medication. LÄS MER

7. 10. Pharmacometric Investigations of Prediction Precision and Advances of Models for Composite Scale Data

   Författare :Gustaf Wellhagen; Maria C. Kjellsson; Bengt Hamrén; Per Olsson Gisleskog; Uppsala universitet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; pharmacometrics; modelling; non-linear mixed effects modelling; composite scale data; total score data; total score analysis; precision prediction; bounded integer; bounded integer model; IRT-informed total score analysis; item response theory-informed; mixed models for repeated measures; MMRM; dose-response; dose-response mixed models for repeated measures; DR-MMRM; HbA1c models; fit-for-purpose analysis; clinical trial analysis; Farmaceutisk vetenskap; Pharmaceutical Science;

   Sammanfattning : Clinical trials are needed to evaluate new treatments. In late-stage clinical trials, failures are mostly due to lack of efficacy. Fit-for-purpose analysis methods will likely increase the success rates and advance drug development by providing higher precision to support decisions such as go/no-go, dose selection, or sample size. LÄS MER