Modeling Evasive Response Bias in Randomized Response: Cheater Detection Versus Self-protective No-Saying.

Randomized response is an interview technique for sensitive questions designed to eliminate evasive response bias. Since this elimination is only partially successful, two models have been proposed for modeling evasive response bias: the cheater detection model for a design with two sub-samples with different randomization probabilities and the self-protective no sayers model for a design with multiple sensitive questions. This paper shows the correspondence between these models, and introduces models for the new, hybrid "ever/last year" design that account for self-protective no saying and cheating.

The analysis of randomized response "ever" and "last year" questions: A non-saturated Multinomial model.

Randomized response (RR) is a well-known interview technique designed to eliminate evasive response bias that arises from asking sensitive questions. The most frequently asked questions in RR are either whether respondents were "ever" carriers of the sensitive characteristic, or whether they were carriers in a recent period, for instance, "last year". The present paper proposes a design in which both questions are asked, and derives a multinomial model for the joint analysis of these two questions.

Refinement of the extended crosswise model with a number sequence randomizer: Evidence from three different studies in the UK.

The Extended Crosswise Model (ECWM) is a randomized response model with neutral response categories, relatively simple instructions, and the availability of a goodness-of-fit test. This paper refines this model with a number sequence randomizer that virtually precludes the possibility to give evasive responses. The motivation for developing this model stems from a strategic priority of WADA (World Anti-Doping Agency) to monitor the prevalence of doping use by elite athletes.

A multilevel structural equation model for assessing a drug effect on a patient-reported outcome measure in on-demand medication data.

We analyze data from a clinical trial investigating the effect of an on-demand drug for women with low sexual desire. These data consist of a varying number of measurements/events across patients of when the drug was taken, including data on a patient-reported outcome consisting of five items measuring an unobserved construct (latent variable). Traditionally, these data are aggregated prior to analysis by composing one sum score per event and averaging this sum score over all observed events.

Functionality of the Crosswise Model for Assessing Sensitive or Transgressive Behavior: A Systematic Review and Meta-Analysis.

Tools for reliable assessment of socially sensitive or transgressive behavior warrant constant development. Among them, the Crosswise Model (CM) has gained considerable attention. We systematically reviewed and meta-analyzed empirical applications of CM and addressed a gap for quality assessment of indirect estimation models.

Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks.

Standard reference terminology of diagnoses and risk factors is crucial for billing, epidemiological studies, and inter/intranational comparisons of diseases. The International Classification of Disease (ICD) is a standardized and widely used method, but the manual classification is an enormously time-consuming endeavor. Natural language processing together with machine learning allows automated structuring of diagnoses using ICD-10 codes, but the limited performance of machine learning models, the necessity of gigantic datasets, and poor reliability of terminal parts of these codes restricted clinical usability.

Prioritising Hepatitis C treatment in people with multiple injecting partners maximises prevention: A real-world network study.

Objective: To describe an injecting network of PWID living in an isolated community on the Isle of Wight (UK) and the results of a agent-based simulation, testing the effect of Hepatitis C (HCV) treatment on transmission.

Method: People who inject drugs (PWID) were identified via respondent driven sampling and recruited to a network and bio-behavioural survey. The injecting network they described formed the baseline population and potential transmission pathways in an agent-based simulation of HCV transmission and the effects of treatment over 12 months.

Multilevel analyses of on-demand medication data, with an application to the treatment of Female Sexual Interest/Arousal Disorder.

Data from clinical trials investigating on-demand medication often consist of an intentionally varying number of measurements per patient. These measurements are often observations of discrete events of when the medication was taken, including for example data on symptom severity. In addition to the varying number of observations between patients, the data have another important feature: they are characterized by a hierarchical structure in which the events are nested within patients.

Optimizing predictive performance of criminal recidivism models using registration data with binary and survival outcomes.

In a recidivism prediction context, there is no consensus on which modeling strategy should be followed for obtaining an optimal prediction model. In previous papers, a range of statistical and machine learning techniques were benchmarked on recidivism data with a binary outcome. However, two important tree ensemble methods, namely gradient boosting and random forests were not extensively evaluated.

Doing philosophy effectively II: A replication and elaboration of student learning in classroom teaching.

An important aim of teaching philosophy in Dutch secondary schools is to learn about philosophy (that is, the great philosophers) by doing philosophy. In an earlier study published in PLoS ONE, we focused on the relationship between student learning activities and teacher behavior by analyzing eight lessons. Correspondence analysis revealed that doing philosophy was more effective in some lessons than in others.

A stochastic simulation model to study respondent-driven recruitment.

Respondent-driven detection is a chain recruitment method used to sample contact persons of infected persons in order to enhance case finding. It starts with initial individuals, so-called seeds, who are invited for participation. Afterwards, seeds receive a fixed number of coupons to invite individuals with whom they had contact during a specific time period.

Psychometric Properties of the Sexual Event Diary in a Sample of Dutch Women With Female Sexual Interest/Arousal Disorder.

Background: Efficacy of on-demand drugs for women with hypoactive sexual desire disorder or female sexual interest/arousal disorder (FSIAD) should be assessed using a validated instrument that assesses the discrete sexual events during which the on-demand drug is taken, because this type of assessment is more proximate to an on-demand drug's efficacy compared to instruments that assess sexual function over longer periods of time.

Aim: The aim of this study was to assess the psychometric properties of the Dutch translation of the previously validated 11-item Sexual Event Diary (SED) for measuring sexual satisfaction and sexual functioning during discrete sexual events.

Methods: Psychometric assessment was performed on data of 1,840 SEDs from 139 women with hypoactive sexual desire disorder/FSIAD, collected during a randomized clinical cross-over trial conducted in the Netherlands.

The Sexual Event Diary (SED): Development and Validation of a Standardized Questionnaire for Assessing Female Sexual Functioning During Discrete Sexual Events.

Background: The efficacy of on-demand drugs for hypoactive sexual desire disorder (HSDD) or female sexual interest/arousal disorder (FSIAD) should be assessed using a validated instrument that assesses the discrete sexual events during which the on-demand drug is taken.

Aim: To develop and validate an event log for measuring sexual satisfaction and sexual functioning of discrete sexual events.

Methods: Psychometric assessment was carried out on data of 10,959 Sexual Event Diaries (SEDs) collected during three clinical trials in a total of 421 women with HSDD.

Tracking social contact networks with online respondent-driven detection: who recruits whom?

Background: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven detection can provide relevant epidemiological data on numbers of contact persons and dynamics of contacts between pairs of individuals.

Doing Philosophy Effectively: Student Learning in Classroom Teaching.

An important aim of teaching philosophy in Dutch secondary schools is to learn about philosophy (i.e., the great philosophers) by doing philosophy.

Distance comparisons in virtual reality: effects of path, context, and age.

In this large scale, individual differences study (N = 521), the effects of cardinal axes of an environment and the path taken between locations on distance comparisons were assessed. The main goal was to identify if and to what extent previous findings in simple 2D tasks can be generalized to a more dynamic, three-dimensional virtual reality environment. Moreover, effects of age and gender were assessed.

Correspondence: Some general points regarding Ledberg and Wennberg, BMC Medical Research Methodology 2014 April 27;14:58.

The purpose of this note is to contribute some general points on a recent paper by Ledberg and Wennberg (BMC Med Res Meth 14:58, 2014) which need to be rectified. They advocate the capture-removal estimator. First, we will discuss drawbacks of this estimator in comparison to the Lincoln-Petersen estimator.

Enhancing Syndromic Surveillance With Online Respondent-Driven Detection.

Objectives: We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants.

Methods: In 2014, volunteers from 2 large panels in the Netherlands were invited to complete a survey focusing on symptoms of upper respiratory tract infections and to invite 4 individuals they had met in the preceding 2 weeks to take part in the study. We compared sociodemographic characteristics among panel participants, individuals who volunteered for our survey, and individuals recruited via respondent-driven detection.

The multidimensional randomized response design: Estimating different aspects of the same sensitive behavior.

The conventional randomized response design is unidimensional in the sense that it measures a single dimension of a sensitive attribute, like its prevalence, frequency, magnitude, or duration. This paper introduces a multidimensional design characterized by categorical questions that each measure a different aspect of the same sensitive attribute. The benefits of the multidimensional design are (i) a substantial gain in power and efficiency, and the potential to (ii) evaluate the goodness-of-fit of the model, and (iii) test hypotheses about evasive response biases in case of a misfit.

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling.

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in The Netherlands and Thailand using a similar online respondent-driven method.

Stability and change of ODD, CD and ADHD diagnosis in referred preschool children.

Longitudinal studies have shown that preschool children's diagnosis of Oppositional Defiant Disorder (ODD), Conduct Disorder (CD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are likely to persist into school age. However, limited attention has been paid to instability of diagnosis. The aim of the present study, therefore, was to investigate both stability and change of ODD, CD and ADHD diagnosis in children aged 3.

Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand.

Background: Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network.