Test equating sleep scales: applying the Leunbach's model.

BACKGROUND: In most cases, the total scores from different instruments assessing the same construct are not directly comparable, but must be equated. In this study we aimed to illustrate a novel test equating methodology applied to sleep functions, a domain in which few score comparability studies exist. METHODS: Eight scales from two cross-sectional self-report studies were considered, and one scale was common to both studies. The International Classification of Functioning, Disability and Health (ICF) was used to establish content comparability. Direct (common persons) and indirect (common item) equating was assessed by means of Leunbach's model, which equates the scores of two scales depending on the same person parameter, taking into account several tests of fit and the Standard Error of Equating (SEE). RESULTS: All items were linked to the body functions category b134 of the ICF, which corresponds to 'Sleep functions'. The scales were classified into three sleep aspects: four scales were assessing mainly sleep disturbance, one quality of sleep, and three impact of sleep on daily life. Of 16 direct equated pairs, 15 could be equated according to Leunbach's model, and of 12 indirect equated pairs, 8 could be equated. Raw score conversion tables between each of these 23 equated pairs are provided. The SEE was higher for indirect than for direct equating. Pairs measuring the same sleep aspect did not show better fit indices than pairs from different aspects. The instruments mapped to a higher order concept of sleep functions. CONCLUSION: Leunbach's equating model has been successfully applied to a functioning domain little explored in test equating. This novel methodology, together with the ICF, enables comparison of clinical outcomes and research results, and facilitates communication among clinicians.

Supporting construct validity of the Evaluation of Daily Activity Questionnaire using Linear Logistic Test Models.

PURPOSE: Construct validity is commonly assessed by applying statistical methods to data. However, purely empirical methods cannot explain what happens between the attribute and the instrument scores, which is the core of construct validity. Linear Logistic Test Models (LLTMs) can provide such explanation by decomposing item difficulties into a weighted sum of theoretical item properties. In this study, we aim to support construct validity of the Evaluation of Daily Activity Questionnaire (EDAQ) by using item properties accounting for item difficulties. METHODS: Dichotomized responses to the EDAQ were analyzed with (1) the Rasch model (to estimate item difficulties), and (2) LLTMs (to predict item difficulties). Seven properties of the items were identified and rated in ordinal scales by 39 Occupational Therapists worldwide. Aggregated metric estimates-the weights used to predict item difficulties in LLTMs-were derived from the ratings using seven cumulative link mixed models. Estimated and predicted item difficulties were compared. RESULTS: The Rasch model showed acceptable fit and unidimensionality for a sample of 42 locally independent EDAQ items. The LLTM plus error showed significantly better fit than the LLTM. In the former, three of the seven properties were not significant, and the corresponding model including only the significant properties was used to predict item difficulties; they explained 77.5% of the variance in estimated item difficulties. CONCLUSION: A satisfactory theoretical explanation of what makes an activity of daily living task more difficult than another has been provided by a LLTM plus error model, therefore supporting construct validity of the EDAQ.

All metrics are equal, but some metrics are more equal than others: A systematic search and review on the use of the term 'metric'.

OBJECTIVE: To examine the use of the term 'metric' in health and social sciences' literature, focusing on the interval scale implication of the term in Modern Test Theory (MTT). MATERIALS AND METHODS: A systematic search and review on MTT studies including 'metric' or 'interval scale' was performed in the health and social sciences literature. The search was restricted to 2001-2005 and 2011-2015. A Text Mining algorithm was employed to operationalize the eligibility criteria and to explore the uses of 'metric'. The paradigm of each included article (Rasch Measurement Theory (RMT), Item Response Theory (IRT) or both), as well as its type (Theoretical, Methodological, Teaching, Application, Miscellaneous) were determined. An inductive thematic analysis on the first three types was performed. RESULTS: 70.6% of the 1337 included articles were allocated to RMT, and 68.4% were application papers. Among the number of uses of 'metric', it was predominantly a synonym of 'scale'; as adjective, it referred to measurement or quantification. Three incompatible themes 'only RMT/all MTT/no MTT models can provide interval measures' were identified, but 'interval scale' was considerably more mentioned in RMT than in IRT. CONCLUSION: 'Metric' is used in many different ways, and there is no consensus on which MTT metric has interval scale properties. Nevertheless, when using the term 'metric', the authors should specify the level of the metric being used (ordinal, ordered, interval, ratio), and justify why according to them the metric is at that level.

Is ADHD in childhood associated with lifetime hoarding symptoms? An epidemiological study.

BACKGROUND: Although hoarding symptoms have been traditionally conceptualized as part of obsessive-compulsive disorder (OCD), recent data suggest that they may be more closely related to attention-deficit hyperactivity (ADHD) symptoms and, in particular, inattention. The aim of the present epidemiological study was to investigate the association between retrospectively reported ADHD symptoms in childhood and lifetime hoarding symptoms. METHODS: Retrospectively reported childhood ADHD, and lifetime hoarding and obsessive-compulsive symptoms were assessed with the Composite International Diagnostic Interview 3.0 in a random subsample of individuals (n = 2,963) participating in a cross-sectional survey of the adult general population of nine European countries, as part of the World Mental Health (WMH) Surveys. RESULTS: Lifetime hoarding symptoms were more common among individuals with childhood ADHD symptoms than those without ADHD symptoms (8.9% versus 2.7%, P = 0.024). Childhood inattention (but not hyperactivity) was associated with lifetime hoarding symptoms (OR = 6.04, 95% CI = 3.59-10.1) and this association remained significant after controlling for the presence of obsessive-compulsive symptoms. CONCLUSION: Longitudinal studies are now needed to explore the hypothesis that inattention symptoms in childhood may be a precursor of hoarding difficulties later in life.

Prescription-drug-related risk in driving: comparing conventional and lasso shrinkage logistic regressions.

BACKGROUND: Large data sets with many variables provide particular challenges when constructing analytic models. Lasso-related methods provide a useful tool, although one that remains unfamiliar to most epidemiologists. METHODS: We illustrate the application of lasso methods in an analysis of the impact of prescribed drugs on the risk of a road traffic crash, using a large French nationwide database (PLoS Med 2010;7:e1000366). In the original case-control study, the authors analyzed each exposure separately. We use the lasso method, which can simultaneously perform estimation and variable selection in a single model. We compare point estimates and confidence intervals using (1) a separate logistic regression model for each drug with a Bonferroni correction and (2) lasso shrinkage logistic regression analysis. RESULTS: Shrinkage regression had little effect on (bias corrected) point estimates, but led to less conservative results, noticeably for drugs with moderate levels of exposure. Carbamates, carboxamide derivative and fatty acid derivative antiepileptics, drugs used in opioid dependence, and mineral supplements of potassium showed stronger associations. CONCLUSION: Lasso is a relevant method in the analysis of databases with large number of exposures and can be recommended as an alternative to conventional strategies.

Analysis of multiple exposures in the case-crossover design via sparse conditional likelihood.

We adapt the least absolute shrinkage and selection operator (lasso) and other sparse methods (elastic net and bootstrapped versions of lasso) to the conditional logistic regression model and provide a full R implementation. These variable selection procedures are applied in the context of case-crossover studies. We study the performances of conventional and sparse modelling strategies by simulations, then empirically compare results of these methods on the analysis of the association between exposure to medicinal drugs and the risk of causing an injurious road traffic crash in elderly drivers. Controlling the false discovery rate of lasso-type methods is still problematic, but this problem is also present in conventional methods. The sparse methods have the ability to provide a global analysis of dependencies, and we conclude that some of the variants compared here are valuable tools in the context of case-crossover studies with a large number of variables.