Anna Gottard

Nonconservative exact small-sample inference for discrete data

Exact small-sample methods for discrete data use probability distributions that do not depend on unknown parameters. However, they are conservative inferentially: the actual error probabilities for tests and confidence intervals are bounded above by the nominal level. This article surveys ways of reducing or even eliminating the conservatism. Fuzzy inference is a recent innovation that enables one to achieve the error probability exactly. We present a simple way of conducting fuzzy inference for discrete one-parameter exponential family distributions. In practice, most scientists would find this approach unsuitable yet might be disappointed by the conservatism of ordinary exact methods. Thus, we recommend using exact small-sample distributions but with inferences based on the mid-P value. This approach can be motivated by fuzzy inference, it is less conservative than standard exact methods, yet usually it does well in terms of achieving desired error probabilities. We illustrate for inferences about the binomial parameter.

Comment: Randomized Confidence Intervals and the Mid-P Approach

We enjoyed reading the interesting, thought-provok ing article by Geyer and Meeden. In our comments we will try to place their work in perspective rela tive to the original proposals for exact and random ized confidence intervals for the binomial parameter. We propose a fuzzy version of the original binomial randomized confidence interval, due to Stevens (1950). Our approach motivates an existing nonrandomized confidence interval based on inverting a test using the mid-P value. The mid-P confidence interval provides a sensible compromise that mitigates the effects of con servatism of exact methods, yet provides results that are more easily understandable to the scientist.

Varying uncertainty in CUB models

This paper presents a generalization of a mixture model used for the analysis of ratings and preferences by introducing a varying uncertainty component. According to the standard mixture model, called CUB model, the response probabilities are defined as a convex combination of shifted Binomial and discrete Uniform random variables. Our proposal introduces uncertainty distributions with different shapes, which could capture response style and indecision of respondents with greater effectiveness. Since we consider several alternative specifications that are nonnested, we suggest the implementation of a Vuong test for choosing among them. In this regard, some simulation experiments and real case studies confirm the usefulness of the approach.

A little elastic for a better performance: kinesiotaping of the motor effector modulates neural mechanisms for rhythmic movements

A rhythmic motor performance is brought about by an integration of timing information with movements. Investigations on the millisecond time scale distinguish two forms of time control, event-based timing and emergent timing. While event-based timing asserts the existence of a central internal timekeeper for the control of repetitive movements, the emergent timing perspective claims that timing emerges from dynamic control of nontemporal movements parameters. We have recently demonstrated that the precision of an isochronous performance, defined as performance of repeated movements having a uniform duration, was insensible to auditory stimuli of various characteristics (Bravi et al., 2014). Such finding has led us to investigate whether the application of an elastic therapeutic tape (Kinesio® Tex taping; KTT) used for treating athletic injuries and a variety of physical disorders, is able to reduce the timing variability of repetitive rhythmic movement. Young healthy subjects, tested with and without KTT, have participated in sessions in which sets of repeated isochronous wrists flexion-extensions (IWFEs) were performed under various auditory conditions and during their recall. Kinematics was recorded and temporal parameters were extracted and analyzed. Our results show that the application of KTT decreases the variability of rhythmic movements by a 2-fold effect: on the one hand KTT provides extra proprioceptive information activating cutaneous mechanoreceptors, on the other KTT biases toward the emergent timing thus modulating the processes for rhythmic movements. Therefore, KTT appears able to render movements less audio dependent by relieving, at least partially, the central structures from time control and making available more resources for an augmented performance.

Robust concentration graph model selection

Concentration graph models are an attractive tool to explore the conditional independence structure in a multivariate normal distribution. In applications, in absence of a priori knowledge, it is possible to select the graph underlying a set of data through an appropriate model selection procedure. The recently proposed procedure, SINful, is appealing but sensitive to outliers, as it utilizes the sample estimator of the covariance matrix. A method to make the SINful procedure robust with respect to the presence of outlying observations, is proposed. This is based on the minimum covariance determinant (MCD) estimator for the variance-covariance matrix. A simulation study shows the advantages of this method.

On the impact of contaminations in graphical Gaussian models

This paper analyzes the impact of some kinds of contaminant on model selection in graphical Gaussian models. We investigate four different kinds of contaminants, in order to consider the effect of gross errors, model deviations, and model misspecification. The aim of the work is to assess against which kinds of contaminant a model selection procedure for graphical Gaussian models has a more robust behavior. The analysis is based on simulated data. The simulation study shows that relatively few contaminated observations in even just one of the variables can have a significant impact on correct model selection, especially when the contaminated variable is a node in a separating set of the graph.

Reducing conservatism of exact small-sample methods of inference for discrete data

Exact small-sample methods for discrete data use probability distributions that do not depend on unknown parameters. However, they are conservative inferentially: The actual error probabilities for tests and confidence intervals are bounded above by the nominal level. This article discusses ways of reducing the conservatism. Fuzzy inference is a recent innovation that enables one to achieve the error probability exactly. We present a simple way of conducting fuzzy inference for discrete one-parameter exponential family distributions. In practice, most scientists would find this approach unsuitable yet might be disappointed by the conservatism of ordinary exact methods. Thus, to use exact small-sample distributions, we recommend inferences based on the mid-P value. This approach can be motivated by fuzzy inference, it is less conservative than standard exact methods, yet usually it does well in terms of achieving desired error probabilities. We illustrate this and other small-sample methods for the case of inferences about the binomial parameter.

A Bayesian approach to model interdependent event histories by graphical models

In event history analysis, the problem of modeling two interdependent processes is still not completely solved. In a frequentist framework, there are two most general approaches: the causal approach and the system approach. The recent growing interest in Bayesian statistics suggests some interesting works on survival models and event history analysis in a Bayesian perspective. In this work we present a possible solution for the analysis of dynamic interdependence by a Bayesian perspective in a graphical duration model framework, using marked point processes. Main results from the Bayesian approach and the comparison with the frequentist one are illustrated on a real example: the analysis of the dynamic relationship between fertility and female employment.

When Non-Dominant Is Better than Dominant: Kinesiotape Modulates Asymmetries in Timed Performance during a Synchronization-Continuation Task

There is a growing consensus regarding the specialization of the non-dominant limb (NDL)/hemisphere system to employ proprioceptive feedback when executing motor actions. In a wide variety of rhythmic tasks the dominant limb (DL) has advantages in speed and timing consistency over the NDL. Recently, we demonstrated that the application of Kinesio® Tex (KT) tape, an elastic therapeutic device used for treating athletic injuries, improves significantly the timing consistency of isochronous wrist’s flexion-extensions (IWFEs) of the DL. We argued that the augmented precision of IWFEs is determined by a more efficient motor control during movements due to the extra-proprioceptive effect provided by KT. In this study, we tested the effect of KT on timing precision of IWFEs performed with the DL and the NDL, and we evaluated the efficacy of KT to counteract possible timing precision difference between limbs. Young healthy subjects performed with and without KT (NKT) a synchronization-continuation task in which they first entrained IWFEs to paced auditory stimuli (synchronization phase), and subsequently continued to produce motor responses with the same temporal interval in the absence of the auditory stimulus (continuation phase). Two inter-onset intervals (IOIs) of 550-ms and 800-ms, one within and the other beyond the boundaries of the spontaneous motor tempo, were tested. Kinematics was recorded and temporal parameters were extracted and analyzed. Our results show that limb advantages in performing proficiently rhythmic movements are not side-locked but depend also on speed of movement. The application of KT significantly reduces the timing variability of IWFEs performed at 550-ms IOI. KT not only cancels the disadvantages of the NDL but also makes it even more precise than the DL without KT. The superior sensitivity of the NDL to use the extra-sensory information provided by KT is attributed to a greater competence of the NDL/hemisphere system to rely on sensory input. The findings in this study add a new piece of information to the context of motor timing literature. The performance asymmetries here demonstrated as preferred temporal environments could reflect limb differences in the choice of sensorimotor control strategies for the production of human movement.

The Less You are, the More You are Helped: Effect of Kinesio Tape on Temporal Coordination

We investigated whether a relationship exists between the inherent timing skill of subject and the magnitude of effect of KT on timing performance by expanding the examination of the dataset described in our previous work. Healthy subjects, tested with and without KT (NKT), performed sets of repetitive wrists flexion-extensions (IWFEs) with the dominant limb (DL) and the non-dominant limb (NDL) in a synchronization-continuation task at two inter-onset intervals (IOIs): 550-ms and 800-ms. Standard deviation (SD) of IWFEs was used to measure the unevenness of performance. Different patterns of response to KT were observed based on the participants inherent precision. In the NDL the effect of KT was found significantly higher in the subgroups of individuals having SDNKT of IWFEs>38 ms (p=0.0024) in the 800-ms IOI or SDNKT of IWFEs>19 ms (p=0.0004) in the 550-ms IOI. In the DL the effect of KT was not influenced by the inherent timing skill. We propose KT to be tested for restoring motor control on subjects experiencing sensorimotor disorders associated with intense repetitive training. Also, our findings suggest that care should be taken when using groups of healthy subjects to test the effect of KT.