Koen Lamberts

Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders

Background Participant drop-out occurs in all longitudinal studies, and if systematic, may lead to selection biases and erroneous conclusions being drawn from a study. Aims We investigated whether drop out in the Avon Longitudinal Study of Parents And Children (ALSPAC) was systematic or random, and if systematic, whether it had an impact on the prediction of disruptive behaviour disorders. Method Teacher reports of disruptive behaviour among currently participating, previously participating and never participating children aged 8 years in the ALSPAC longitudinal study were collected. Data on family factors were obtained in pregnancy. Simulations were conducted to explain the impact of selective drop-out on the strength of prediction. Results Drop out from the ALSPAC cohort was systematic and children who dropped out were more likely to suffer from disruptive behaviour disorder. Systematic participant drop-out according to the family variables, however, did not alter the association between family factors obtained in pregnancy and disruptive behaviour disorder at 8 years of age. Conclusions Cohort studies are prone to selective drop-out and are likely to underestimate the prevalence of psychiatric disorder. This empirical study and the simulations confirm that the validity of regression models is only marginally affected despite range restrictions after selective drop-out.

Eating Problems at Age 6 Years in a Whole Population Sample of Extremely Preterm Children.

Aim  The aim of this study was to investigate the prevalence of eating problems and their association with neurological and behavioural disabilities and growth among children born extremely preterm (EPC) at age 6 years.

The encoding–retrieval relationship: retrieval as mental simulation

There is increasing evidence to suggest that mental simulations underlie many cognitive processes. We review results from three rapidly developing research areas suggesting that simulations underlie information retrieval. First, neuroimaging work indicates that cortical circuits that were activated during encoding are reactivated during retrieval. Second, retrieval is aided by behavioural re-enactment of processes involved in encoding, including re-enactment of encoding eye movements. Third, the time courses of encoding of visual features and the retrieval of information about those features are related. Overall, the evidence suggests that the often observed interactions between encoding and retrieval result from a cognitive system that, at least partially, reactivates processes that were involved in encoding to retrieve information.

A feature-sampling account of the time course of old-new recognition judgments

This article describes the feature-sampling theory of recognition (FESTHER), a new model of the time course of recognition judgments based on a model of the time course of perceptual processing in categorization (K. Lamberts, 1995, 1998). FESTHER is applied to previous results and to data from 4 old-new recognition experiments. Experiments 1 and 2 provided a preliminary test of the models ability to explain recognition judgments of simple objects under response deadlines. Experiments 3 and 4 involved a response-signal procedure to elicit recognition judgments at different time lags after presentation of a stimulus. Simple objects and words were used as stimuli in Experiments 3 and 4, respectively. The new model accounts well for the data from the 4 experiments and offers a parsimonious account of the time course of recognition judgments based on the time-dependent availability of stimulus information.

Feature-sampling and random-walk models of individual-stimulus recognition.

Traditional process models of old-new recognition have not addressed differences in accuracy and response time between individual stimuli. Two new process models of recognition are presented and applied to response time and accuracy data from 3 old-new recognition experiments. The 1st model is derived from a feature-sampling account of the time course of categorization, whereas the 2nd model is a generalization of a random-walk model of categorization. In the experiments, a new technique was used, which yielded reliable individual-stimulus data through repeated presentation of structurally equivalent items. The results from the experiments showed reliable differences in accuracy and response times between stimuli. The random-walk model provided the better account of the results from the 3 experiments. The implications of the results for process models of recognition are discussed.

An Exemplar Account of the Bow and Set-Size Effects in Absolute Identification.

The extended generalized context model for response times (K. Lamberts, 2000) was designed to account for choice proportions and response times in perceptual categorization. In this article, the hypothesis that the model also offers an account of accuracy and response times in absolute identification was investigated. The model was applied to the data from 2 absolute identification experiments and provided a good account of the bow and the set-size effects in accuracy and response time data from individual participants, including the response time distributions for individual stimuli. The model applications demonstrated that exemplar-based process models offer a viable account of absolute identification data.

Adaptive changes of response criterion in recognition memory

An experiment was conducted to investigate people’s ability to vary a response criterion strategically, in a recognition memory task, as a function of the length of time given to process the test stimuli (from 100 to 1,500 msec). The experiment used the response signal procedure, in which the participants responded after a signal that came at a variable time delay from stimulus onset. The proportion of new versus old test items was varied systematically with the time of the response signal, with the proportion of new test items rising, falling, or staying constant at later signals. It was found that the participants’ response biases changed adaptively, becoming more conservative at later signals in the rising condition, becoming less conservative in the falling condition, and not changing significantly in the constant condition. Theoretical and methodological implications for recognition memory research are discussed.

Feature sampling in categorization and recognition of objects

This article presents an overview of some recent work on the time course of perceptual categorization and recognition memory. First, The EGCM-RT, which is a feature-sampling model of the time course of categorization, is described. It is shown that the model explains a wide range of categorization data. Second, an overview is given of a feature-sampling model of the time course of recognition that is derived from the EGCM-RT. This model explains results that have been interpreted in the past as evidence for dual-process models of recognition, and it provides a single-process alternative to dual-process accounts.

Guidelines for usable cybersecurity: Past and present

Usability is arguably one of the most significant social topics and issues within the field of cybersecurity today. Supported by the need for confidentiality, integrity, availability and other concerns, security features have become standard components of the digital environment which pervade our lives requiring use by novices and experts alike. As security features are exposed to wider cross-sections of the society, it is imperative that these functions are highly usable. This is especially because poor usability in this context typically translates into inadequate application of cybersecurity tools and functionality, thereby ultimately limiting their effectiveness. With this goal of highly usable security in mind, there have been a plethora of studies in the literature focused on identifying security usability problems and proposing guidelines and recommendations to address them. Our paper aims to contribute to the field by consolidating a number of existing design guidelines and defining an initial core list for future reference. Whilst investigating this topic, we take the opportunity to provide an up-to-date review of pertinent cybersecurity usability issues and evaluation techniques applied to date. We expect this research paper to be of use to researchers and practitioners with interest in cybersecurity systems which appreciate the human and social elements of design.

Perceptual processes in matching and recognition of complex pictures

The role of perceptual feature sampling in speeded matching and recognition was explored in 4 experiments. Experiments 1-3 involved a perceptual matching task with pictures of various objects and scenes. In Experiments 2 and 3, same-different judgments were given under time pressure. The main objective of the matching task was to obtain measures of the perceptual processing rates of different object features. Experiment 4 was an old-new recognition experiment, in which the same stimuli as those in the matching task were used. Response signals were used to limit processing time in the recognition task. The results demonstrated that it is possible to predict speeded recognition performance from performance in perceptual matching. A simple stochastic feature-sampling model provides a unified account of the data from the 4 experiments.