Assessing Fit of the Lognormal Model for Response Times

2020 ◽  
Vol 45 (5) ◽  
pp. 534-568
Author(s):  
Sandip Sinharay ◽  
Peter W. van Rijn
Keyword(s):  
Factor Analysis ◽  
Response Time ◽  
Simulation Study ◽  
Response Times ◽  
Real Data ◽  
Psychological Testing ◽  
Response Time Models ◽  
Lognormal Model ◽  
Analysis Models

Response time models (RTMs) are of increasing interest in educational and psychological testing. This article focuses on the lognormal model for response times, which is one of the most popular RTMs. Several existing statistics for testing normality and the fit of factor analysis models are repurposed for testing the fit of the lognormal model. A simulation study and two real data examples demonstrate the usefulness of the statistics. The Shapiro–Wilk test of normality and a z-test for factor analysis models were the most powerful in assessing the misfit of the lognormal model.

Lumped-Parameter Response Time Models for Pneumatic Circuit Dynamics

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Andrew A. Stanley ◽  
Amirhossein Amini ◽  
Casey Glick ◽  
Nathan Usevitch ◽  
Yiğit Mengüç ◽  
...  
Keyword(s):  
Response Time ◽  
High Speed ◽  
Response Times ◽  
Coefficient Of Determination ◽  
Response Time Models ◽  
Response Curves ◽  
Flow Restriction ◽  
Lumped Parameter ◽  
Fluidic Circuits ◽  
Timing Models

Abstract Resistor–capacitor (RC) response time models for pressurizing and depressurizing a pneumatic capacitor (mass accumulator) through a resistor (flow restriction) comprise a framework to systematically analyze complex fluidic circuits. A model for pneumatic resistance is derived from a combination of fundamental fluid mechanics and experimental results. Models describing compressible fluid capacitance are derived from thermodynamic first principles and validated experimentally. The models are combined to derive the ordinary differential equations that describe the RC dynamics. These equations are solved analytically for rigid capacitors and numerically for deformable capacitors to generate pressure response curves as a function of time. The dynamic pressurization and depressurization response times to reach 63.2% (or 1−e−1) of exponential decay are validated in simple pneumatic circuits with combinations of flow restrictions ranging from 100 μm to 1 mm in diameter, source pressures ranging from 5 to 200 kPa, and capacitor volumes of 0.5 to 16 mL. Our RC models predict the response times, which range from a few milliseconds to multiple seconds depending on the combination, with a coefficient of determination of r2=0.983. The utility of the models is demonstrated in a multicomponent fluidic circuit to find the optimal diameter of tubing between a three-way electromechanical valve and a pneumatic capacitor to minimize the response time for the changing pressure in the capacitor. These lumped-parameter models represent foundational blocks upon which timing models of pneumatic circuits can be built for a variety of applications from soft robotics and industrial automation to high-speed microfluidics.

scholarly journals Transforming variables to central normality

2021 ◽  
Author(s):  
Jakob Raymaekers ◽  
Peter J. Rousseeuw
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimator ◽  
Simulation Study ◽  
Real Data ◽  
Data Sets ◽  
Transformation Parameter ◽  
Likelihood Estimator ◽  
Extensive Simulation ◽  
Highly Sensitive

AbstractMany real data sets contain numerical features (variables) whose distribution is far from normal (Gaussian). Instead, their distribution is often skewed. In order to handle such data it is customary to preprocess the variables to make them more normal. The Box–Cox and Yeo–Johnson transformations are well-known tools for this. However, the standard maximum likelihood estimator of their transformation parameter is highly sensitive to outliers, and will often try to move outliers inward at the expense of the normality of the central part of the data. We propose a modification of these transformations as well as an estimator of the transformation parameter that is robust to outliers, so the transformed data can be approximately normal in the center and a few outliers may deviate from it. It compares favorably to existing techniques in an extensive simulation study and on real data.

Using a Response Time–Based Expected A Posteriori Estimator to Control for Differential Speededness in Computerized Adaptive Test

2021 ◽  
pp. 014662162110146
Author(s):  
Justin L. Kern ◽  
Edison Choe
Keyword(s):  
Response Times ◽  
Real Data ◽  
Joint Estimation ◽  
Item Selection ◽  
A Posteriori ◽  
Computerized Adaptive Test ◽  
Maximum Information ◽  
Adaptive Test ◽  
Estimation And Control ◽  
And Control

This study investigates using response times (RTs) with item responses in a computerized adaptive test (CAT) setting to enhance item selection and ability estimation and control for differential speededness. Using van der Linden’s hierarchical framework, an extended procedure for joint estimation of ability and speed parameters for use in CAT is developed following van der Linden; this is called the joint expected a posteriori estimator (J-EAP). It is shown that the J-EAP estimate of ability and speededness outperforms the standard maximum likelihood estimator (MLE) of ability and speededness in terms of correlation, root mean square error, and bias. It is further shown that under the maximum information per time unit item selection method (MICT)—a method which uses estimates for ability and speededness directly—using the J-EAP further reduces average examinee time spent and variability in test times between examinees above the resulting gains of this selection algorithm with the MLE while maintaining estimation efficiency. Simulated test results are further corroborated with test parameters derived from a real data example.

scholarly journals Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

2017 ◽  
Vol 29 (5) ◽  
pp. 529-542 ◽  
Author(s):  
Marko Intihar ◽  
Tomaž Kramberger ◽  
Dejan Dragan
Keyword(s):  
Factor Analysis ◽  
Goodness Of Fit ◽  
Moving Average ◽  
Real Data ◽  
Information Criteria ◽  
Dynamic Factor Analysis ◽  
Forecasting Model ◽  
Dynamic Factor ◽  
Macroeconomic Indicators ◽  
The Impact

The paper examines the impact of integration of macroeconomic indicators on the accuracy of container throughput time series forecasting model. For this purpose, a Dynamic factor analysis and AutoRegressive Integrated Moving-Average model with eXogenous inputs (ARIMAX) are used. Both methodologies are integrated into a novel four-stage heuristic procedure. Firstly, dynamic factors are extracted from external macroeconomic indicators influencing the observed throughput. Secondly, the family of ARIMAX models of different orders is generated based on the derived factors. In the third stage, the diagnostic and goodness-of-fit testing is applied, which includes statistical criteria such as fit performance, information criteria, and parsimony. Finally, the best model is heuristically selected and tested on the real data of the Port of Koper. The results show that by applying macroeconomic indicators into the forecasting model, more accurate future throughput forecasts can be achieved. The model is also used to produce future forecasts for the next four years indicating a more oscillatory behaviour in (2018-2020). Hence, care must be taken concerning any bigger investment decisions initiated from the management side. It is believed that the proposed model might be a useful reinforcement of the existing forecasting module in the observed port.

A novel hybrid method for improving ambulance dispatching response time through a simulation study

2016 ◽  
Vol 60 ◽  
pp. 170-184 ◽  
Author(s):  
Mehdi Zarkeshzadeh ◽  
Hadi Zare ◽  
Zainabolhoda Heshmati ◽  
Mehdi Teimouri
Keyword(s):  
Response Time ◽  
Simulation Study ◽  
Hybrid Method

scholarly journals Stimulus-response time to invasive blood pressure alarms: implications for the safety of critical-care patients

2014 ◽  
Vol 35 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Adele Kuckartz Pergher ◽  
Roberto Carlos Lyra da Silva
Keyword(s):  
Blood Pressure ◽  
Response Time ◽  
Response Times ◽  
Hemodynamic Instability ◽  
Military Hospital ◽  
Invasive Blood Pressure ◽  
Stimulus Response ◽  
The City ◽  
Physical Layout

Observational, descriptive, exploratory, case study with the objective of measuring the stimulus-response time of the team to alarms monitoring invasive blood pressure (IBP) and analyzing the implications of this time for the safety of the patient. From January to March 2013, 60 hours of structured observation were conducted with registration of the alarms activated by IBP monitors in an adult ICU at a military hospital in the city of Rio de Janeiro. 76 IBP alarms were recorded (1.26 alarms/hour), 21 of which (28%) were attended to and 55 (72%) considered as fatigued. The average response time to the alarms was 2 min. 45 sec. The deficit in human resource and physical layout were factors determining the delay in response to the alarms. The increase in response times to these alarms may compromise the safety of patients with hemodynamic instability, especially in situations such as shock and the use of vasoactive drugs.

scholarly journals English Speakers’ Implicit Gender Concepts Influence Their Processing of French Grammatical Gender: Evidence for Semantically Mediated Cross-Linguistic Influence

2021 ◽  
Vol 12 ◽  
Author(s):  
Elena Nicoladis ◽  
Chris Westbury ◽  
Cassandra Foursha-Stevenson
Keyword(s):  
Second Language ◽  
Response Time ◽  
Response Times ◽  
First Language ◽  
Grammatical Gender ◽  
Word Embedding ◽  
English Speakers ◽  
French Words ◽  
L1 English ◽  
French Gender

Second language (L2) learners often show influence from their first language (L1) in all domains of language. This cross-linguistic influence could, in some cases, be mediated by semantics. The purpose of the present study was to test whether implicit English gender connotations affect L1 English speakers’ judgments of the L2 French gender of objects. We hypothesized that gender estimates derived from word embedding models that measure similarity of word contexts in English would affect accuracy and response time on grammatical gender (GG) decision in L2 French. L2 French learners were asked to identify the GG of French words estimated to be either congruent or incongruent with the implicit gender in English. The results showed that they were more accurate with words that were congruent with English gender connotations than words that were incongruent, suggesting that English gender connotations can influence grammatical judgments in French. Response times showed the same pattern. The results are consistent with semantics-mediated cross-linguistic influence.

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