On the Speed Sensitivity Parameter in the Lognormal Model for Response Times and Implications for High-Stakes Measurement Practice

In high-stakes testing, often multiple test forms are used and a common time limit is enforced. Test fairness requires that ability estimates must not depend on the administration of a specific test form. Such a requirement may be violated if speededness differs between test forms. The impact of not taking speed sensitivity into account on the comparability of test forms regarding speededness and ability estimation was investigated. The lognormal measurement model for response times by van der Linden was compared with its extension by Klein Entink, van der Linden, and Fox, which includes a speed sensitivity parameter. An empirical data example was used to show that the extended model can fit the data better than the model without speed sensitivity parameters. A simulation was conducted, which showed that test forms with different average speed sensitivity yielded substantial different ability estimates for slow test takers, especially for test takers with high ability. Therefore, the use of the extended lognormal model for response times is recommended for the calibration of item pools in high-stakes testing situations. Limitations to the proposed approach and further research questions are discussed.

An adaptive q-Lognormal model towards the computation of Average Channel Capacity in slow fading channels

The characterization of multipath fading and shadowing in wireless communication systems is essential towards the evaluation of various performance measures. It is well known that the statistical characterization of shadowing phenomena is captured by distributions viz., log-normal distribution, gamma distribution and other mixture distributions. However, it is observed that the log-normal distribution fails to characterize the outliers in the fading signal. The extreme fluctuations in the fading signal needs to be characterized efficiently for error free computation of the various performance metrics. In this context, this paper portrays an adaptive generalized Tsallis’ non-extensive q-Lognormal model towards the characterization of various fading channels. This model operates well with the synthesized fading signals and captures the wide range of tail fluctuations to adapt different fading scenarios. The significance and applicability of the proposed novel q- Lognormal model in capturing the slow fading channels is validated using different statistical tests viz., chi-square test and symmetric JS measure. Furthermore, essential performance measures viz., the average channel capacity, closed form expression of cumulative distribution function (CDF) in terms of Gauss-Hypergeometric function 2 F 1 [a ; b ; c; z], higher order moments corresponding to q-Lognormal channel capacity and coefficient of variation is evaluated corresponding to the proposed q-Lognormal model performing extensive Monte-Carlo simulation techniques up to O (10^7).

Exposure-Based Models of Trail User Crashes at Roadway Crossings

Multi-use trails are popular for transportation and recreation, but pedestrians and bicyclists are exposed to motor vehicle traffic at trail crossings (locations where trails cross roadways), creating the risk of crashes, injuries, and fatalities. Many trail crossing design guidelines suggest best practices to make trail crossings safe, but few studies have quantified the statistical relationship between trail user crashes and a broad set of trail crossing characteristics. Our study developed one of the first trail crossing crash models using trail user crashes reported at 197 crossings in the city of Minneapolis, MN, and in the Milwaukee, WI, region between 2011 and 2018. We took advantage of widespread trail counting programs and historic aerial and street-level imagery to create and test more than 30 theoretically important potential explanatory variables. We addressed the challenge that many crossings had small numbers of crashes (or zero crashes) during the study period by using a Poisson-lognormal model. Our model showed significant associations between trail crossing crashes and trail traffic volume, roadway motor vehicle volume, three-way intersections where the trail crosses perpendicular to the mainline roadway, and total crossing length. Although not statistically significant, signalized intersections and limited sight lines between drivers and trail users near crossings may also be associated with more crashes. Future research can build on this study and expand systemic efforts to improve trail crossing safety.

Sigma-Lognormal Modeling of Speech

Human movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition to robotics, health care to sports, and beyond. Previous speech motor models were proposed to understand how speech movement is produced and how the resulting speech varies when some parameters are changed. However, the inverse approach, in which the muscular response parameters and the subject’s age are derived from real continuous speech, is not possible with such models. Instead, in the handwriting field, the kinematic theory of rapid human movements and its associated Sigma-lognormal model have been applied successfully to obtain the muscular response parameters. This work presents a speech kinematics-based model that can be used to study, analyze, and reconstruct complex speech kinematics in a simplified manner. A method based on the kinematic theory of rapid human movements and its associated Sigma-lognormal model are applied to describe and to parameterize the asymptotic impulse response of the neuromuscular networks involved in speech as a response to a neuromotor command. The method used to carry out transformations from formants to a movement observation is also presented. Experiments carried out with the (English) VTR-TIMIT database and the (German) Saarbrucken Voice Database, including people of different ages, with and without laryngeal pathologies, corroborate the link between the extracted parameters and aging, on the one hand, and the proportion between the first and second formants required in applying the kinematic theory of rapid human movements, on the other. The results should drive innovative developments in the modeling and understanding of speech kinematics.