Naïve Tests of Basic Local Independence Model’s Invariance

2015 ◽  
Vol 18 ◽  
Author(s):  
Debora de Chiusole ◽  
Luca Stefanutti ◽  
Pasquale Anselmi ◽  
Egidio Robusto
Keyword(s):  
Simulation Study ◽  
Empirical Data ◽  
Statistical Tests ◽  
Local Independence ◽  
Data Set ◽  
Independence Model ◽  
Knowledge States ◽  
Specific Assumption ◽  
Basic Local Independence Model ◽  
Theoretical Results

AbstractThe basic local independence model (BLIM) is a probabilistic model for knowledge structures, characterized by the property that lucky guess and careless error parameters of the items are independent of the knowledge states of the subjects. When fitting the BLIM to empirical data, a good fit can be obtained even when the invariance assumption is violated. Therefore, statistical tests are needed for detecting violations of this specific assumption. This work provides an extension to theoretical results obtained by de Chiusole, Stefanutti, Anselmi, and Robusto (2013), showing that statistical tests based on the partitioning of the empirical data set into two (or more) groups are not adequate for testing the BLIM’s invariance assumption. A simulation study confirms the theoretical results.

scholarly journals Extending the Basic Local Independence Model to Polytomous Data

Psychometrika ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. 684-715
Author(s):  
Luca Stefanutti ◽  
Debora de Chiusole ◽  
Pasquale Anselmi ◽  
Andrea Spoto
Keyword(s):  
Learning Assessment ◽  
Model Parameters ◽  
Local Independence ◽  
Data Set ◽  
True Parameter ◽  
Independence Model ◽  
Study Results ◽  
Minimum Discrepancy ◽  
Basic Local Independence Model ◽  
Parameter Values

Abstract A probabilistic framework for the polytomous extension of knowledge space theory (KST) is proposed. It consists in a probabilistic model, called polytomous local independence model, that is developed as a generalization of the basic local independence model. The algorithms for computing “maximum likelihood” (ML) and “minimum discrepancy” (MD) estimates of the model parameters have been derived and tested in a simulation study. Results show that the algorithms differ in their capability of recovering the true parameter values. The ML algorithm correctly recovers the true values, regardless of the manipulated variables. This is not totally true for the MD algorithm. Finally, the model has been applied to a real polytomous data set collected in the area of psychological assessment. Results show that it can be successfully applied in practice, paving the way to a number of applications of KST outside the area of knowledge and learning assessment.

Can Mouse-tracking Reveal Attribute Processing Speeds in Dietary Self-control? Commentary on Sullivan et al. (2015) and Lim et al. (2018) with A Simulation Study

2018 ◽  
Author(s):  
Chao Zhang ◽  
Martijn Willemsen ◽  
Daniel Lakens
Keyword(s):  
Simulation Study ◽  
Processing Speed ◽  
Empirical Data ◽  
Self Control ◽  
Alternative Mechanism ◽  
Mouse Tracking ◽  
Tracking Method ◽  
Cognitive Mechanism ◽  
Speed Difference ◽  
Original Hypothesis

In this commentary, we re-examine the use of a mouse-tracking method for revealing attribute processing speed difference in dietary self-control (Sullivan et al. 2015; Lim et al., 2018). Through re-analyses of Sullivan et al. (2015)’s data and a simulation study, it can be shown that the attribute-angle correlations in the empirical data, which were used to estimate processing speeds, are attributed primarily to their common correlations with choice. The simulation study further suggests that when we account for the choice-mediated attribute-angle correlations, the data patterns used for supporting the original hypothesis can be produced by implementing a plausible alternative mechanism unrelated to processing speeds. The mouse-tracking method therefore fails to provide clear evidence for processing speed difference as a cognitive mechanism of self-control. Researchers should be cautious when using the mouse-tracking method to estimate attribute processing speeds.

scholarly journals Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings

2014 ◽  
Vol 112 (11) ◽  
pp. 2729-2744 ◽  
Author(s):  
Carlo J. De Luca ◽  
Joshua C. Kline
Keyword(s):  
Motor Unit ◽  
Statistical Tests ◽  
Vastus Lateralis ◽  
Common Input ◽  
Data Set ◽  
Order Of Magnitude ◽  
Score Method ◽  
Surface Electromyographic Signal ◽  
Measure Synchronization

Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles—a data set one order of magnitude greater than that reported in previous studies. Only firing data, obtained from surface electromyographic signal decomposition with >95% accuracy, were used in the study. The data were not subjectively selected in any manner. Because of the size of our data set and the statistical rigor inherent to SigMax, we have confidence that the synchronization values that we calculated provide an improved estimate of physiologically driven synchronization. Compared with three other commonly used techniques, ours revealed three types of discrepancies that result from failing to use sufficient statistical tests necessary to detect synchronization. 1) On average, the z-score method falsely detected synchronization at 16 separate latencies in each motor-unit pair. 2) The cumulative sum method missed one out of every four synchronization identifications found by SigMax. 3) The common input assumption method identified synchronization from 100% of motor-unit pairs studied. SigMax revealed that only 50% of motor-unit pairs actually manifested synchronization.

scholarly journals Computer Modelling For 4-Stroke Direct Injection Diesel Engine

2008 ◽  
Vol 33-37 ◽  
pp. 801-806
Author(s):  
Abdul Rahim Ismail ◽  
Rosli Abu Bakar ◽  
Semin Ali ◽  
Ismail Ali
Keyword(s):  
Diesel Engine ◽  
Simulation Study ◽  
Engine Speed ◽  
Computer Modelling ◽  
Direct Injection ◽  
One Dimension ◽  
Effective Pressure ◽  
Operational Parameters ◽  
Direct Injection Diesel Engine ◽  
Theoretical Results

Study on computational modeling of 4-stroke single cylinder direct injection diesel engine is presented. The engine with known specification is being modeled using one dimension CFD GT-Power software. The operational parameters of the engine such as power, torque, specific fuel consumption and mean effective pressure which are dependent to engine speed are being discussed. The results from the simulation study are compared with the theoretical results to get the true trend of the results.

Design Chaotic Neural Network from Discrete Time Feedback Function

2013 ◽  
Vol 339 ◽  
pp. 366-371
Author(s):  
Jin Sheng Ren ◽  
Guang Chun Luo ◽  
Ke Qin
Keyword(s):  
Discrete Time ◽  
Design Methodology ◽  
Universal Design ◽  
Jacobian Matrix ◽  
Sufficient Conditions ◽  
Neural Net ◽  
Chaotic Neural Network ◽  
Data Set ◽  
Dominant Matrix ◽  
Theoretical Results

The goal of this paper is to give a universal design methodology of a Chaotic Neural Net-work (CNN). By appropriately choosing self-feedback, coupling functions and external stimulus, we have succeeded in proving a dynamical system defined by discrete time feedback equations possess-ing interesting chaotic properties. The sufficient conditions of chaos are analyzed by using Jacobian matrix, diagonal dominant matrix and Lyapunov Exponent (LE). Experiments are also conducted un-der a simple data set. The results confirm the theorem's correctness. As far as we know, both the experimental and theoretical results presented here are novel.

scholarly journals Organic aerosol source apportionment in London 2013 with ME-2: exploring the solution space with annual and seasonal analysis

2016 ◽  
Vol 16 (24) ◽  
pp. 15545-15559 ◽  
Author(s):  
Ernesto Reyes-Villegas ◽  
David C. Green ◽  
Max Priestman ◽  
Francesco Canonaco ◽  
Hugh Coe ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Statistical Tests ◽  
Solution Space ◽  
Organic Aerosol ◽  
Data Sets ◽  
Environmental Implications ◽  
Data Set ◽  
Diesel Vehicles ◽  
Heavy Duty Diesel ◽  
Paul Scherrer

Abstract. The multilinear engine (ME-2) factorization tool is being widely used following the recent development of the Source Finder (SoFi) interface at the Paul Scherrer Institute. However, the success of this tool, when using the a value approach, largely depends on the inputs (i.e. target profiles) applied as well as the experience of the user. A strategy to explore the solution space is proposed, in which the solution that best describes the organic aerosol (OA) sources is determined according to the systematic application of predefined statistical tests. This includes trilinear regression, which proves to be a useful tool for comparing different ME-2 solutions. Aerosol Chemical Speciation Monitor (ACSM) measurements were carried out at the urban background site of North Kensington, London from March to December 2013, where for the first time the behaviour of OA sources and their possible environmental implications were studied using an ACSM. Five OA sources were identified: biomass burning OA (BBOA), hydrocarbon-like OA (HOA), cooking OA (COA), semivolatile oxygenated OA (SVOOA) and low-volatility oxygenated OA (LVOOA). ME-2 analysis of the seasonal data sets (spring, summer and autumn) showed a higher variability in the OA sources that was not detected in the combined March–December data set; this variability was explored with the triangle plots f44 : f43 f44 : f60, in which a high variation of SVOOA relative to LVOOA was observed in the f44 : f43 analysis. Hence, it was possible to conclude that, when performing source apportionment to long-term measurements, important information may be lost and this analysis should be done to short periods of time, such as seasonally. Further analysis on the atmospheric implications of these OA sources was carried out, identifying evidence of the possible contribution of heavy-duty diesel vehicles to air pollution during weekdays compared to those fuelled by petrol.

Replication of Data Analyses

2017 ◽  
Author(s):  
Emery R. Boose ◽  
Barbara S. Lerner
Keyword(s):  
Original Work ◽  
Statistical Tests ◽  
Scientific Paper ◽  
Scientific Data ◽  
Data Sources ◽  
Narrative Form ◽  
Data Provenance ◽  
General Description ◽  
Data Set ◽  
Data Analyses

The metadata that describe how scientific data are created and analyzed are typically limited to a general description of data sources, software used, and statistical tests applied and are presented in narrative form in the methods section of a scientific paper or a data set description. Recognizing that such narratives are usually inadequate to support reproduction of the analysis of the original work, a growing number of journals now require that authors also publish their data. However, finer-scale metadata that describe exactly how individual items of data were created and transformed and the processes by which this was done are rarely provided, even though such metadata have great potential to improve data set reliability. This chapter focuses on the detailed process metadata, called “data provenance,” required to ensure reproducibility of analyses and reliable re-use of the data.

scholarly journals Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data

Demography ◽  
2021 ◽  
Vol 58 (1) ◽  
pp. 51-74
Author(s):  
Lee Fiorio ◽  
Emilio Zagheni ◽  
Guy Abel ◽  
Johnathan Hill ◽  
Gabriel Pestre ◽  
...  
Keyword(s):  
Empirical Data ◽  
Survival Function ◽  
The United States ◽  
Population Characteristics ◽  
Phone Call ◽  
Research Strategies ◽  
Data Set ◽  
Trace Data ◽  
Transition Functions ◽  
Temporal Granularity

Abstract Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide a general framework for converting digital trace data into estimates of migration transitions and for systematically analyzing their variation along a quasi-continuous time scale, analogous to a survival function. From migration theory, we develop two simple hypotheses regarding how we expect our estimated migration transition functions to behave. We then test our hypotheses on simulated data and empirical data from three platforms in two internal migration contexts: geotagged Tweets and Gowalla check-ins in the United States, and cell-phone call detail records in Senegal. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research. At the same time, however, common patterns across our three empirical data sets point to an emergent research agenda using digital trace data to study the specific functional relationship between estimates of migration and time and how this relationship varies by geography and population characteristics.

scholarly journals Variations in optical properties of aerosols on monsoon seasonal change and estimation of aerosol optical depth using ground-based meteorological and air quality data

2014 ◽  
Vol 14 (13) ◽  
pp. 19747-19789
Author(s):  
F. Tan ◽  
H. S. Lim ◽  
K. Abdullah ◽  
T. L. Yoon ◽  
B. Holben
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Statistical Tests ◽  
Air Pollutant ◽  
Quality Data ◽  
Supplementary Information ◽  
Northeast Monsoon ◽  
Data Set ◽  
Proposed Model

Abstract. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the aerosol optical depth (AOD) against the Angstrom exponent. A modified algorithm based on the prototype model of Tan et al. (2014a) was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET because of frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The predicted AOD of the model was generated based on the coefficients and compared against the measured data through standard statistical tests. The predicted AOD in the proposed model yielded a coefficient of determination R2 of 0.68. The corresponding percent mean relative error was less than 0.33% compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Validation tests were performed on the model against selected LIDAR data and yielded good correspondence. The predicted AOD can beneficially monitor short- and long-term AOD and provide supplementary information in atmospheric corrections.

scholarly journals Exploring a model-based analysis of patient derived xenograft studies in oncology drug development

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10681
Author(s):  
Jake Dickinson ◽  
Marcel de Matas ◽  
Paul A. Dickinson ◽  
Hitesh B. Mistry
Keyword(s):  
Simulation Study ◽  
Statistical Power ◽  
Tumour Growth ◽  
Empirical Approach ◽  
Series Data ◽  
Ratio Test ◽  
Data Set ◽  
Model Based ◽  
Patient Derived Xenograft ◽  
Model Based Analysis

Purpose To assess whether a model-based analysis increased statistical power over an analysis of final day volumes and provide insights into more efficient patient derived xenograft (PDX) study designs. Methods Tumour xenograft time-series data was extracted from a public PDX drug treatment database. For all 2-arm studies the percent tumour growth inhibition (TGI) at day 14, 21 and 28 was calculated. Treatment effect was analysed using an un-paired, two-tailed t-test (empirical) and a model-based analysis, likelihood ratio-test (LRT). In addition, a simulation study was performed to assess the difference in power between the two data-analysis approaches for PDX or standard cell-line derived xenografts (CDX). Results The model-based analysis had greater statistical power than the empirical approach within the PDX data-set. The model-based approach was able to detect TGI values as low as 25% whereas the empirical approach required at least 50% TGI. The simulation study confirmed the findings and highlighted that CDX studies require fewer animals than PDX studies which show the equivalent level of TGI. Conclusions The study conducted adds to the growing literature which has shown that a model-based analysis of xenograft data improves statistical power over the common empirical approach. The analysis conducted showed that a model-based approach, based on the first mathematical model of tumour growth, was able to detect smaller size of effect compared to the empirical approach which is common of such studies. A model-based analysis should allow studies to reduce animal use and experiment length providing effective insights into compound anti-tumour activity.

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