A Rasch model for partial credit scoring

<b>brms</b> : An <i>R</i> Package for Bayesian Multilevel Models Using <i>Stan</i>

Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476 · see citing works

Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets

van Hout, B., Janssen, M. F., Feng, Y.-S., Kohlmann, T., Busschbach, J., Golicki, D., Lloyd, A., Scalone, L., Kind, P., & Pickard, A. S. (2012) · Value in Health · doi:10.1016/j.jval.2012.02.008 · Cited by 2,153 · see citing works

Untitled work

Tufford (2017) · doi:10.1007/s · Cited by 2,003 · see citing works

Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): a Rasch analysis using data from the Scottish Health Education Population Survey

Stewart-Brown, S., Tennant, A., Tennant, R., Platt, S., Parkinson, J., & Weich, S. (2009) · Health and Quality of Life Outcomes · doi:10.1186/1477-7525-7-15 · Cited by 1,251 · see citing works

Ordinal Regression Models in Psychology: A Tutorial

Bürkner, P.-C., & Vuorre, M. (2019) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245918823199 · Cited by 689 · see citing works

Internal construct validity of the Shirom-Melamed Burnout questionnaire (SMBQ)

Lundgren-Nilsson, Å., Jonsdottir, I. H., Pallant, J., & Ahlborg, G. (2012) · BMC Public Health · doi:10.1186/1471-2458-12-1 · Cited by 626 · see citing works

Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment

Meyer, O. A., Omdahl, M. K., & Makransky, G. (2019) · Computers &amp; Education · doi:10.1016/j.compedu.2019.103603 · Cited by 515 · see citing works

Measuring social isolation in older adults: Development and initial validation of the Friendship Scale

Hawthorne, G. (2006) · Social Indicators Research · doi:10.1007/s11205-005-7746-y · Cited by 450 · see citing works

Development and validation of the Multimodal Presence Scale for virtual reality environments: A confirmatory factor analysis and item response theory approach

Makransky, G., Lilleholt, L., & Aaby, A. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.02.066 · Cited by 424 · see citing works

Construct validity and reliability of the Rivermead Post-Concussion Symptoms Questionnaire

Eyres, S., Carey, A., Gilworth, G., Neumann, V., & Tennant, A. (2005) · Clinical Rehabilitation · doi:10.1191/0269215505cr905oa · Cited by 335 · see citing works

Improving biotech education through gamified laboratory simulations

Bonde, M. T., Makransky, G., Wandall, J., Larsen, M. V., Morsing, M., Jarmer, H., & Sommer, M. O. A. (2014) · Nature Biotechnology · doi:10.1038/nbt.2955 · Cited by 243 · see citing works

The WHO-5 well-being index – validation based on item response theory and the analysis of measurement invariance across 35 countries

Sischka, P. E., Costa, A. P., Steffgen, G., & Schmidt, A. F. (2020) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2020.100020 · Cited by 245 · see citing works

Virtual simulations as preparation for lab exercises: Assessing learning of key laboratory skills in microbiology and improvement of essential non-cognitive skills

Makransky, G., Thisgaard, M. W., & Gadegaard, H. (2016) · PLOS ONE · doi:10.1371/journal.pone.0155895 · Cited by 212 · see citing works

Evaluating the metacognitive awareness inventory using empirical factor-structure evidence

Harrison, G. M., & Vallin, L. M. (2018) · Metacognition and Learning · doi:10.1007/s11409-017-9176-z · Cited by 182 · see citing works

Dimensionality and norms of the Rosenberg Self-Esteem Scale in a German general population sample

Roth, M., Decker, O., Herzberg, P. Y., & Brähler, E. (2008) · European Journal of Psychological Assessment · doi:10.1027/1015-5759.24.3.190 · Cited by 166 · see citing works

A conceptual and psychometric framework for distinguishing categories and dimensions

De Boeck, P., Wilson, M., & Acton, G. S. (2005) · Psychological Review · doi:10.1037/0033-295x.112.1.129 · Cited by 131 · see citing works

Machine learning–driven language assessment

Settles, B., T. LaFlair, G., & Hagiwara, M. (2020) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00310 · Cited by 106 · see citing works

Response categories and anger measurement: do fewer categories result in poorer measurement?: Development of the DAR5

Hawthorne, G., Mouthaan, J., Forbes, D., & Novaco, R. W. (2006) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-005-0986-y · Cited by 77 · see citing works

Evaluating Equivalency Between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D

Pickard, A. S., Kohlmann, T., Janssen, M. F., Bonsel, G., Rosenbloom, S., & Cella, D. (2007) · Medical Care · doi:10.1097/mlr.0b013e31805371aa · Cited by 66 · see citing works

Supporting digitally enhanced learning through measurement in higher education: Development and validation of a university students' digital competence scale

Wang, X., Wang, Z., Wang, Q., Chen, W., & Pi, Z. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12546 · Cited by 62 · see citing works

Teacher-Directed Versus Inquiry-Based Science Instruction: Investigating Links to Adolescent Students’ Science Dispositions Across 66 Countries

Areepattamannil, S., Cairns, D., & Dickson, M. (2020) · Journal of Science Teacher Education · doi:10.1080/1046560x.2020.1753309 · Cited by 59 · see citing works

Sleep quality prediction in caregivers using physiological signals

Sadeghi, R., Banerjee, T., Hughes, J. C., & Lawhorne, L. W. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.05.010 · Cited by 50 · see citing works

Validating a multiple mini-interview question bank assessing entry-level reasoning skills in candidates for graduate-entry medicine and dentistry programmes

Roberts, C., Zoanetti, N., & Rothnie, I. (2009) · Medical Education · doi:10.1111/j.1365-2923.2009.03292.x · Cited by 49 · see citing works

Development of a Short Version of MSQOL-54 Using Factor Analysis and Item Response Theory

Rosato, R., Testa, S., Bertolotto, A., Confalonieri, P., Patti, F., Lugaresi, A., Grasso, M. G., Toscano, A., Giordano, A., & Solari, A. (2016) · PLOS ONE · doi:10.1371/journal.pone.0153466 · Cited by 46 · see citing works

A New Questionnaire for Estimating the Severity of Visual Height Intolerance and Acrophobia by a Metric Interval Scale

Huppert, D., Grill, E., & Brandt, T. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00211 · Cited by 46 · see citing works

Rasch Analysis of the Profiles of Occupational Engagement in people with Severe mental illness (POES) instrument

Bejerholm, U., & Lundgren-Nilsson, Å. (2015) · Health and Quality of Life Outcomes · doi:10.1186/s12955-015-0327-0 · Cited by 39 · see citing works

A generalized many-facet Rasch model and its Bayesian estimation using Hamiltonian Monte Carlo

Uto, M., & Ueno, M. (2020) · Behaviormetrika · doi:10.1007/s41237-020-00115-7 · Cited by 37 · see citing works

Evaluating composite health measures using Rasch modelling: An illustrative example

Hagquist, C. (2001) · Sozial- und Präventivmedizin SPM · doi:10.1007/bf01321663 · Cited by 34 · see citing works

The Fear Avoidance Beliefs Questionnaire (FABQ) Does it Really Measure Fear Beliefs?

Aasdahl, L., Marchand, G. H., Gismervik, S. Ø., Myhre, K., Fimland, M. S., & Røe, C. (2020) · Spine · doi:10.1097/brs.0000000000003188 · Cited by 34 · see citing works

Measuring activities of daily living in Parkinson’s disease: On a road to nowhere and back again?

Hagell, P. (2019) · Measurement · doi:10.1016/j.measurement.2018.09.050 · Cited by 23 · see citing works

Measuring Engagement in Later Life Activities: Rasch-Based Scenario Scales for Work, Caregiving, Informal Helping, and Volunteering

Ludlow, L. H., Matz-Costa, C., Johnson, C., Brown, M., Besen, E., & James, J. B. (2014) · Measurement and Evaluation in Counseling and Development · doi:10.1177/0748175614522273 · Cited by 22 · see citing works

Die anwendbarkeit des BDI-II in klinischen und nichtklinischen populationen aus psychometrischer sicht. eine vergleichende analyse mit dem rasch-modell.

Alexandrowicz, R. W., Fritzsche, S., & Keller, F. (2014) · Neuropsychiatrie · doi:10.1007/s40211-014-0104-z · Cited by 20 · see citing works

No negative Flynn effect in France: Why variations of intelligence should not be assessed using tests based on cultural knowledge

Gonthier, C., Grégoire, J., & Besançon, M. (2021) · Intelligence · doi:10.1016/j.intell.2020.101512 · Cited by 20 · see citing works

A Bayesian many-facet Rasch model with Markov modeling for rater severity drift

Uto, M. (2022) · Behavior Research Methods · doi:10.3758/s13428-022-01997-z · Cited by 19 · see citing works

Rasch Analysis of Lebanese Nurses’ Responses to the Copenhagen Burnout Inventory Alternative to the Maslach Burnout Inventory

Clinton, M., & Shehadeh, M. (2021) · SAGE Open Nursing · doi:10.1177/23779608211020919 · Cited by 14 · see citing works

Artificial Intelligence Attitudes Inventory (AIAI): Development and Validation Using Rasch Methodology

Krägeloh, C. U., Melekhov, V., Alyami, M. M., & Medvedev, O. N. (2024) · doi:10.21203/rs.3.rs-4403120/v1 · Cited by 13 · see citing works

Artificial Intelligence Attitudes Inventory (AIAI): development and validation using Rasch methodology

Krägeloh, C. U., Melekhov, V., Alyami, M. M., & Medvedev, O. N. (2025) · Current Psychology · doi:10.1007/s12144-025-08009-1 · Cited by 13 · see citing works

Adaptation and Validation of the Cognitive and Affective Mindfulness Scale-Revised (CAMS-R) in People Living with HIV in Myanmar

Huang, F., Chen, W.-T., Shiu, C.-S., Lin, S. H., Tun, M. S., Nwe, T. W., Nu Oo, Y. T., & Oo, H. N. (2022) · Mindfulness · doi:10.1007/s12671-021-01784-5 · Cited by 11 · see citing works

Modeling Effects of Faking on an Objective Personality Test

Arendasy, M., Sommer, M., Herle, M., Schützhofer, B., & Inwanschitz, D. (2011) · Journal of Individual Differences · doi:10.1027/1614-0001/a000053 · Cited by 10 · see citing works

A computerized adaptive testing advancing the measurement of subjective well-being

Wu, Y., Cai, Y., & Tu, D. (2019) · Journal of Pacific Rim Psychology · doi:10.1017/prp.2019.6 · Cited by 8 · see citing works

Top Three Healthcare Trends in Orthopaedics Affecting Musculoskeletal Care in the Elderly

Lorio, M. P., Lewandrowski, K.-U., & Blum, K. (2025) · Current Aging Science · doi:10.2174/0118746098309054240721180720 · Cited by 2 · see citing works