Variable Response Model Research Articles

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine-A New Model Focusing on Electromagnetic Signaling.

The role of signalling in initiating and perpetuating effects triggered by deposition of ionising radiation energy in parts of a system is very clear. Less clear are the very early steps involved in converting energy to chemical and biological effects in non-targeted parts of the system. The paper aims to present a new model, which could aid our understanding of the role of low dose effects in determining ultimate disease outcomes. We propose a key role for electromagnetic signals resulting from physico-chemical processes such as excitation decay, and acoustic waves. These lead to the initiation of damage response pathways such as elevation of reactive oxygen species and membrane associated changes in key ion channels. Critically, these signalling pathways allow coordination of responses across system levels. For example, depending on how these perturbations are transduced, adverse or beneficial outcomes may predominate. We suggest that by appreciating the importance of signalling and communication between multiple levels of organisation, a unified theory could emerge. This would allow the development of models incorporating time, space and system level to position data in appropriate areas of a multidimensional domain. We propose the use of the term “infosome” to capture the nature of radiation-induced communication systems which include physical as well as chemical signals. We have named our model “the variable response model” or “VRM” which allows for multiple outcomes following exposure to low doses or to signals from low dose irradiated cells, tissues or organisms. We suggest that the use of both dose and infosome in radiation protection might open up new conceptual avenues that could allow intrinsic uncertainty to be embraced within a holistic protection framework.

Consensus theory for multiple latent traits and consensus groups

We consider a situation in which a group of respondents answers a set of questions and the aim is to identify any consensus among the respondents—that is, shared attitudes, beliefs, or knowledge. Consensus theory postulates that a latent trait determines the respondents’ probability to produce the consensus response. We propose a new version of the variable-response model, which implements consensus theory for numerical continuous responses, ordered categorical responses, unordered categorical responses, or a mixture thereof. The new model also accounts for multiple consensus groups and multiple latent traits underlying the response data. In a series of simulation studies, we identify procedures and conditions that permit an accurate estimation of the number of consensus groups and latent traits. In these simulations, we find that the model recovers the data-generating consensus responses well. We replicate these findings with the empirical data of a memory test.

Consensus theory for mixed response formats

Measuring shared beliefs, expert consensus, or the details of a crime in eyewitness testimony represents a psychometric challenge. In expert interviews, for example, the correct responses representing the expert consensus (i.e., the answer key) are initially unknown and experts may differ in their contribution to this consensus. I propose the variable-response model, an extension of latent-trait models. The model allows the estimation of the answer key and the latent trait for continuous, categorical, or mixed responses. I describe some minimal requirements for the addition of new response formats to the model. I further propose a Markov chain Monte Carlo algorithm to estimate the model parameters. The results of a simulation study demonstrate that the algorithm accurately recovers the data-generating parameters. I also present an application of the variable-response model to the empirical data of a Geography test. In this application, the parameter estimates correspond well with the true answer key.

Exposure-response modeling using latent variables for the efficacy of a JAK3 inhibitor administered to rheumatoid arthritis patients

Currently, no general methods have been developed to relate pharmacologically based models, such as indirect response models, to discrete or ordered categorical data. We propose the use of an unobservable latent variable (LV), through which indirect response models can be linked with drug exposure. The resulting indirect latent variable response model (ILVRM) is demonstrated using a case study of a JAK3 inhibitor, which was administered to patients in a rheumatoid arthritis (RA) study. The clinical endpoint for signs and symptoms in RA is the American College of Rheumatology response criterion of 20%--a binary response variable. In this case study, four exposure-response models, which have different pharmacological interpretations, were constructed and fitted using the ILVRM method. Specifically, two indirect response models, an effect compartment model, and a model which assumes instantaneous (direct) drug action were assessed and compared for their ability to predict the response data. In general, different model interpretations can influence drug inference, such as time to drug effect onset, as well as affect extrapolations of responses to untested experimental conditions, and the underlying pharmacology that operates to generate key response features does not change because the response was measured discretely. Consideration of these model interpretations can impact future study designs and ultimately provide greater insight into drug development strategies.

Olfactory host location and learning in the granary weevil parasitoidLariophagus distinguendus (Hymenoptera: Pteromalidae)

The sources of volatiles that attract the parasitoid Lariophagus distinguendus(Forst.) to its hosts, the larvae of the granary weevil Sitophilus granarius(L.) infesting grains of Triticum aestivumL., were investigated in bioassays. The influence of oviposition experience on the responsiveness of the parasitoids to the sources of volatiles was considered. The potential sources of attractants are the host larvae, their feces, and the grain infested by the host. Weevil larvae were not attractive. Feces were attractive to females without and females with oviposition experience. Infested grains from which the larvae and feces were removed were slightly attractive to inexperienced, but very attractive to experienced females. Healthy and artificially damaged grains were attractive to experienced parasitoids only. Refering to the “variable response model,” we discuss the effect of experience on the response of the parasitoids to the several stimuli. Stimuli from different trophic levels are used by the foraging parasitoids: feces of the host larvae is an important source of attractants, but also the grains, particularly after experience.

Effects of Host Plant Experience on Foraging Behavior of the Predatory Mite Phytoseiulus persimilis (Acari: Phytoseiidae)

The influence of predator experience on foraging responses by the predatory mite, Phytoseiulus persimilis Athias-Henriot, to stimuli from lima bean and rose leaves with or without residues of Tetranychus urticae Koch, were studied in the laboratory using two-choice tests. Starved P. persimilis females that were born and reared on T. urticaeinfested bean leaves spent more time on bean than on rose leaves with T. urticae residues, although this response was not significant when predators were well fed. Regardless of hunger level, predators with prior experience on rose leaves showed no plant preference. However, P. persimilis females that were born and reared on one plant species (bean or rose) but were subsequently exposed to the other plant species (rose or bean) for 5 d as adults showed no preference for either plant species, regardless of their experiences. P. persimilis females that were born on rose but reared on bean leaves spent more time on bean than on rose, whereas female predators that were born on bean but reared on rose showed no preference for either plant species. When uninfested bean or rose leaves were used, P. persimilis females with prior experience on bean showed no plant preference, regardless of feeding state, whereas well-fed predators with prior experience on rose leaves spent more time on rose than on bean. It was concluded that (1) experience by P. persimilis on different host plants affected predator foraging behavior; (2) stimuli from both prey and host plant were involved; (3) postembryonic experience of the present generation, rather than the experience of the parent generations or where the eggs were laid, affected predator foraging behavior; and (4) foraging responses were influenced by hunger state. The results of this study support two hypotheses of the variable-response model for foraging behavior.

A variable-response model for parasitoid foraging behavior

An important factor inducing variability in foraging behavior in parasitic wasps is experience gained by the insect. Together with the insect's genetic constitution and physiological state, experience ultimately defines the behavioral repertoire under specified environmental circumstances. We present a conceptual variable-response model based on several major observations of a foraging parasitoid's responses to stimuli involved in the hostfinding process. These major observations are that (1) different stimuli evoke different responses or levels of response, (2) strong responses are less variable than weak ones, (3) learning can change response levels, (4) learning increases originally low responses more than originally high responses, and (5) hostderived stimuli serve as rewards in associative learning of other stimuli. The model specifies how the intrinsic variability of a response will depend on the magnitude of the response and predicts when and how learning will modify the insect's behavior. Additional hypotheses related to the model concern how experience with a stimulus modifies behavioral responses to other stimuli, how animals respond in multistimulus situations, which stimuli act to reinforce behavioral responses to other stimuli in the learning process, and finally, how generalist and specialist species differ in their behavioral plasticity. We postulate that insight into behavioral variability in the foraging behavior of natural enemies may be a help, if not a prerequisite, for the efficient application of parasitoids in pest management.

Seasonal Electricity Demand and Pricing Analysis with a Variable Response Model

To forecast accurately the welfare gains and effects on demand from introducing seasonal electricity rates, we use a variable response model with data from the Los Angeles Electricity Rate Study. The model exploits the time series and cross sectional variation in the data and permits household-specific response to hot and cold weather and in the permanent level of consumption. The full information maximum likelihood estimates permit more flexible and accurate forecasts as well as appropriate test statistics. We find that price elasticity is small but significant and that it increases with hotter weather. There are important differences among subpopulations, but the overall welfare gain appears very small in absolute terms and small when compared with the gains from introducing time-of-day pricing estimatedfrom the TOD component of the Los Angeles study.