Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies

Background The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this ‘missing heritability’ have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms. Methodology We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants. Conclusion We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99

On environment difficulty and discriminating power

The final publication is available at Springer via http://dx.doi.org/10.1007/s10458-014-9257-1This paper presents a way to estimate the difficulty and discriminating power of any task instance. We focus on a very general setting for tasks: interactive (possibly multiagent) environments where an agent acts upon observations and rewards. Instead of analysing the complexity of the environment, the state space or the actions that are performed by the agent, we analyse the performance of a population of agent policies against the task, leading to a distribution that is examined in terms of policy complexity. This distribution is then sliced by the algorithmic complexity of the policy and analysed through several diagrams and indicators. The notion of environment response curve is also introduced, by inverting the performance results into an ability scale. We apply all these concepts, diagrams and indicators to two illustrative problems: a class of agent-populated elementary cellular automata, showing how the difficulty and discriminating power may vary for several environments, and a multiagent system, where agents can become predators or preys, and may need to coordinate. Finally, we discuss how these tools can be applied to characterise (interactive) tasks and (multi-agent) environments. These characterisations can then be used to get more insight about agent performance and to facilitate the development of adaptive tests for the evaluation of agent abilities.I thank the reviewers for their comments, especially those aiming at a clearer connection with the field of multi-agent systems and the suggestion of better approximations for the calculation of the response curves. The implementation of the elementary cellular automata used in the environments is based on the library 'CellularAutomaton' by John Hughes for R [58]. 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Assessment and Etiology of Attention Deficit Hyperactivity Disorder and Oppositional Defiant Disorder in Boys and Girls

Attention deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) are more common in boys than girls. In this paper, we investigated whether the prevalence differences are attributable to measurement bias. In addition, we examined sex differences in the genetic and environmental influences on variation in these behaviors. Teachers completed the Conners Teacher Rating Scale-Revised:Short version (CTRS-R:S) in a sample of 800 male and 851 female 7-year-old Dutch twins. No sex differences in the factor structure of the CTRS-R:S were found, implying the absence of measurement bias. The heritabilities for both ADHD and ODD were high and were the same in boys and girls. However, partly different genes are expressed in boys and girls

Response shift in patient-reported outcomes:definition, theory, and a revised model

International audiencePurpose The extant response shift definitions and theoretical response shift models, while helpful, also introduce predicaments and theoretical debates continue. To address these predicaments and stimulate empirical research, we propose a more specific formal definition of response shift and a revised theoretical model. Methods This work is an international collaborative effort and involved a critical assessment of the literature. Results Three main predicaments were identified. First, the formal definitions of response shift need further specification and clarification. Second, previous models were focused on explaining change in the construct intended to be measured rather than explaining the construct at multiple time points and neglected the importance of using at least two time points to investigate response shift. Third, extant models do not explicitly distinguish the measure from the construct. Here we define response shift as an effect occurring whenever observed change (e.g., change in patient-reported outcome measures (PROM) scores) is not fully explained by target change (i.e., change in the construct intended to be measured). The revised model distinguishes the measure (e.g., PROM) from the underlying target construct (e.g., quality of life) at two time points. The major plausible paths are delineated, and the underlying assumptions of this model are explicated. Conclusion It is our hope that this refined definition and model are useful in the further development of response shift theory. The model with its explicit list of assumptions and hypothesized relationships lends itself for critical, empirical examination. Future studies are needed to empirically test the assumptions and hypothesized relationships

A proof of principle for using adaptive testing in routine Outcome Monitoring: the efficiency of the Mood and Anxiety Symptoms Questionnaire -Anhedonic Depression CAT

<p>Abstract</p> <p>Background</p> <p>In Routine Outcome Monitoring (ROM) there is a high demand for short assessments. Computerized Adaptive Testing (CAT) is a promising method for efficient assessment. In this article, the efficiency of a CAT version of the Mood and Anxiety Symptom Questionnaire, - Anhedonic Depression scale (MASQ-AD) for use in ROM was scrutinized in a simulation study.</p> <p>Methods</p> <p>The responses of a large sample of patients (<it>N </it>= 3,597) obtained through ROM were used. The psychometric evaluation showed that the items met the requirements for CAT. In the simulations, CATs with several measurement precision requirements were run on the item responses as if they had been collected adaptively.</p> <p>Results</p> <p>CATs employing only a small number of items gave results which, both in terms of depression measurement and criterion validity, were only marginally different from the results of a full MASQ-AD assessment.</p> <p>Conclusions</p> <p>It was concluded that CAT improved the efficiency of the MASQ-AD questionnaire very much. The strengths and limitations of the application of CAT in ROM are discussed.</p

Some recommendations for developing multidimensional computerized adaptive tests for patient-reported outcomes

PURPOSE: Multidimensional item response theory and computerized adaptive testing (CAT) are increasingly used in mental health, quality of life (QoL), and patient-reported outcome measurement. Although multidimensional assessment techniques hold promises, they are more challenging in their application than unidimensional ones. The authors comment on minimal standards when developing multidimensional CATs. METHODS: Prompted by pioneering papers published in QLR, the authors reflect on existing guidance and discussions from different psychometric communities, including guidelines developed for unidimensional CATs in the PROMIS project. RESULTS: The commentary focuses on two key topics: (1) the design, evaluation, and calibration of multidimensional item banks and (2) how to study the efficiency and precision of a multidimensional item bank. The authors suggest that the development of a carefully designed and calibrated item bank encompasses a construction phase and a psychometric phase. With respect to efficiency and precision, item banks should be large enough to provide adequate precision over the full range of the latent constructs. Therefore CAT performance should be studied as a function of the latent constructs and with reference to relevant benchmarks. Solutions are also suggested for simulation studies using real data, which often result in too optimistic evaluations of an item bank's efficiency and precision. DISCUSSION: Multidimensional CAT applications are promising but complex statistical assessment tools which necessitate detailed theoretical frameworks and methodological scrutiny when testing their appropriateness for practical applications. The authors advise researchers to evaluate item banks with a broad set of methods, describe their choices in detail, and substantiate their approach for validation

Assessing the adequacy of self-reported alcohol abuse measurement across time and ethnicity: cross-cultural equivalence across Hispanics and Caucasians in 1992, non-equivalence in 2001–2002

<p>Abstract</p> <p>Background</p> <p>Do estimates of alcohol abuse reflect true levels across United States Hispanics and non-Hispanic Caucasians, or does culturally-based, systematic measurement error (i.e., measurement bias) affect estimates? Likewise, given that recent estimates suggest alcohol abuse has increased among US Hispanics, the field should also ask, "Does cross-ethnic change in alcohol abuse across time reflect true change or does measurement bias influence change estimates?"</p> <p>Methods</p> <p>To address these questions, I used confirmatory factor analyses for ordered-categorical measures to probe for measurement bias on two large, standardized, nationally representative, US surveys of alcohol abuse conducted in 1992 and 2001–2002. In 2001–2002, analyses investigated whether 10 items operationalizing DSM-IV alcohol abuse provided equivalent measurement across Hispanic (<it>n </it>= 4,893) and non-Hispanic Caucasians (<it>n </it>= 16,480). In 1992, analyses examined whether a reduced 6 item item-set provided equivalent measurement among 834 Hispanic and 14,8335 non-Hispanic Caucasians.</p> <p>Results</p> <p>In 1992, findings demonstrated statistically significant measurement bias for two items. However, sensitivity analyses showed that item-level bias did not appreciably bias item-set based alcohol abuse estimates among this cohort. For 2001–2002, results demonstrated statistically significant bias for seven items, suggesting caution regarding the cross-ethnic equivalence of alcohol abuse estimates among the current US Hispanic population. Sensitivity analyses indicated that item-level differences <it>did </it>erroneously impact alcohol abuse rates in 2001–2002, underestimating rates among Hispanics relative to Caucasians.</p> <p>Conclusion</p> <p>1992's item-level findings suggest that estimates of drinking related social or legal problems may underestimate these specific problems among Hispanics. However, impact analyses indicated no appreciable effect on alcohol abuse estimates resulting from the item-set. Efforts to monitor change in alcohol abuse diagnoses among the Hispanic community can use 1992 estimates as a valid baseline. In 2001–2002, item-level measurement bias on seven items did affect item-set based estimates. Bias underestimated Hispanics' self-reported alcohol abuse levels relative to non-Hispanic Caucasians. Given the cross-ethnic equivalence of 1992 estimates, bias in 2001–2002 speciously minimizes current increases in drinking behavior evidenced among Hispanics. Findings call for increased public health efforts among the Hispanic community and underscore the necessity for cultural sensitivity when generalizing measures developed in the majority to minorities.</p