Semi-automated Rasch analysis with differential item functioning.

Rasch analysis is a procedure to develop and validate instruments that aim to measure a person's traits. However, manual Rasch analysis is a complex and time-consuming task, even more so when the possibility of differential item functioning (DIF) is taken into consideration. Furthermore, manual Rasch analysis by construction relies on a modeler's subjective choices. As an alternative approach, we introduce a semi-automated procedure that is based on the optimization of a new criterion, called in-plus-out-of-questionnaire log likelihood with differential item functioning (IPOQ-LL-DIF), which extends our previous criterion. We illustrate our procedure on artificially generated data as well as on several real-world datasets containing potential DIF items. On these real-world datasets, our procedure found instruments with similar clinimetric properties as those suggested by experts through manual analyses.

Potential mechanisms of the fatigue-reducing effect of cognitive-behavioral therapy in cancer survivors: Three randomized controlled trials.

OBJECTIVE: Fatigue is a common symptom among cancer survivors that can be successfully treated with cognitive-behavioral therapy (CBT). Insights into the working mechanisms of CBT are currently limited. The aim of this study was to investigate whether improvements in targeted cognitive-behavioral variables and reduced depressive symptoms mediate the fatigue-reducing effect of CBT. METHODS: We pooled data from three randomized controlled trials that tested the efficacy of CBT to reduce severe fatigue. In all three trials, fatigue severity (checklist individual strength) decreased significantly following CBT. Assessments were conducted pre-treatment and 6 months later. Classical mediation analysis testing a pre-specified model was conducted and its results compared to those of causal discovery, an explorative data-driven approach testing all possible causal associations and retaining the most likely model. RESULTS: Data from 250 cancer survivors (n = 129 CBT, n = 121 waitlist) were analyzed. Classical mediation analysis suggests that increased self-efficacy and decreased fatigue catastrophizing, focusing on symptoms, perceived problems with activity and depressive symptoms mediate the reduction of fatigue brought by CBT. Conversely, causal discovery and post-hoc analyses indicate that fatigue acts as mediator, not outcome, of changes in cognitions, sleep disturbance and depressive symptoms. CONCLUSIONS: Cognitions, sleep disturbance and depressive symptoms improve during CBT. When assessed pre- and post-treatment, fatigue acts as a mediator, not outcome, of these improvements. It seems likely that the working mechanism of CBT is not a one-way causal effect but a dynamic reciprocal process. Trials integrating intermittent assessments are needed to shed light on these mechanisms and inform optimization of CBT.

autoRasch: An R Package to Do Semi-Automated Rasch Analysis.

The R package autoRasch has been developed to perform a Rasch analysis in a (semi-)automated way. The automated part of the analysis is achieved by optimizing the so-called in-plus-out-of-questionnaire log-likelihood (IPOQ-LL) or IPOQ-LL-DIF when differential item functioning (DIF) is included. These criteria measure the quality of fit on a pre-collected survey, depending on which items are included in the final instrument. To compute these criteria, autoRasch fits the generalized partial credit model (GPCM) or the generalized partial credit model with differential item functioning (GPCM-DIF) using penalized joint maximum likelihood estimation (PJMLE). The package further allows the user to reevaluate the output of the automated method and use it as a basis for performing a manual Rasch analysis and provides standard statistics of Rasch analyses (e.g., outfit, infit, person separation reliability, and residual correlation) to support the model reevaluation.

Development and validation of the patient-reported "Facial Function Scale" for facioscapulohumeral muscular dystrophy.

PURPOSE: Facial weakness and its functional consequences are an often underappreciated clinical feature of facioscapulohumeral muscular dystrophy (FSHD) by healthcare professionals and researchers. This is at least in part due to the fact that there are few adequate clinical outcome measures available. METHODS: We developed the Facial Function Scale, a Rasch-built questionnaire on the functional disabilities relating to facial weakness in FSHD. A preliminary 33-item questionnaire was created based on semi-structured interviews with 16 FSHD patients and completed by 119 patients. For reliability studies, 73 patients completed it again after a two-week interval. Data were subjected to semi-automated Rasch analysis to select the most appropriate item set to fit model expectations. RESULTS: This resulted in a 25-item unidimensional, linear-weighted questionnaire with high internal consistency (person separation index = 0.92) and test-retest reliability (patients' locations ICC = 0.98 and items' locations ICC = 0.99). Good external construct validity scores were obtained through correlation with the Communicative Participation Item Bank questionnaire, examiner-reported Facial Weakness Score and facial weakness subscale of the FSHD evaluation score (respectively r = 0.733, r = -0.566, and r = 0.441, all p < 0.001). CONCLUSIONS: This study provides a linear-weighted, clinimetrically sound, patient-reported outcome measure on the functional disabilities relating to facial weakness in FSHD, to enable further research on this relevant topic.Implications for rehabilitationFacial weakness and its functional consequences are an often underappreciated clinical feature of facioscapulohumeral muscular dystrophy (FSHD), both in symptomatic treatment and in research.To enable the development and testing of therapeutic symptomatic interventions for facial weakness, clinical outcome measures are required.This study provides a linear-weighted, clinimetrically sound, patient-reported outcome measure on the functional disabilities relating to facial weakness in FSHD patients.

Semi-automated Rasch analysis using in-plus-out-of-questionnaire log likelihood.

Rasch analysis is a popular statistical tool for developing and validating instruments that aim to measure human performance, attitudes and perceptions. Despite the availability of various software packages, constructing a good instrument based on Rasch analysis is still considered to be a complex, labour-intensive task, requiring human expertise and rather subjective judgements along the way. In this paper we propose a semi-automated method for Rasch analysis based on first principles that reduces the need for human input. To this end, we introduce a novel criterion, called in-plus-out-of-questionnaire log likelihood (IPOQ-LL). On artificial data sets, we confirm that optimization of IPOQ-LL leads to the desired behaviour in the case of multi-dimensional and inhomogeneous surveys. On three publicly available real-world data sets, our method leads to instruments that are, for all practical purposes, indistinguishable from those obtained by Rasch analysis experts through a manual procedure.