scholarly journals Delineating the Average Rate of Change in Longitudinal Models

2008 ◽  
Vol 33 (3) ◽  
pp. 307-332 ◽  
Author(s):  
Ken Kelley ◽  
Scott E. Maxwell
Keyword(s):  
Longitudinal Data ◽  
Empirical Data ◽  
Average Rate ◽  
Rate Of Change ◽  
Change Model ◽  
Individual Change ◽  
Longitudinal Models ◽  
Data Set ◽  
Straight Line ◽  
Two Measures

The average rate of change is a concept that has been misunderstood in the literature. This article attempts to clarify the concept and show unequivocally the mathematical definition and meaning of the average rate of change in longitudinal models. The slope from the straight-line change model has at times been interpreted as if it were always the average rate of change. It is shown, however, that this is generally not the case and holds true in only a limited number of situations. General equations are presented for two measures of discrepancy when the slope from the straight-line change model is used to estimate the average rate of change. The importance of fitting an appropriate individual change model is discussed, as are the benefits provided by models nonlinear in their parameters for longitudinal data. An empirical data set is used to illustrate the analytic developments.

Measures Collected on the USMA Class of 1998 as Part of the Baseline Officer Longitudinal Data Set (BOLDS)

2002 ◽  
Author(s):  
Lynn M. Milan ◽  
Dennis R. Bourne ◽  
Michelle M. Zazanis ◽  
Paul T. Bartone
Keyword(s):  
Longitudinal Data ◽  
Data Set

scholarly journals Weight Feedback-Based Harmonic MDG-Ensemble Model for Prediction of Traffic Accident Severity

2021 ◽  
Vol 11 (11) ◽  
pp. 5072
Author(s):  
Byung-Kook Koo ◽  
Ji-Won Baek ◽  
Kyung-Yong Chung
Keyword(s):  
Traffic Accidents ◽  
Average Rate ◽  
Modern Society ◽  
Rate Of Change ◽  
Weighted Voting ◽  
Independent Variables ◽  
Dependent Variables ◽  
Accident Severity ◽  
Harmonic Average ◽  
Bagging Method

Traffic accidents are emerging as a serious social problem in modern society but if the severity of an accident is quickly grasped, countermeasures can be organized efficiently. To solve this problem, the method proposed in this paper derives the MDG (Mean Decrease Gini) coefficient between variables to assess the severity of traffic accidents. Single models are designed to use coefficient, independent variables to determine and predict accident severity. The generated single models are fused using a weighted-voting-based bagging method ensemble to consider various characteristics and avoid overfitting. The variables used for predicting accidents are classified as dependent or independent and the variables that affect the severity of traffic accidents are predicted using the characteristics of causal relationships. Independent variables are classified as categorical and numerical variables. For this reason, a problem arises when the variation among dependent variables is imbalanced. Therefore, a harmonic average is applied to the weights to maintain the variables’ balance and determine the average rate of change. Through this, it is possible to establish objective criteria for determining the severity of traffic accidents, thereby improving reliability.

Tie Decay and Dissolution: Contentious Prescribing Practices in the Prescription Drug Epidemic

2021 ◽  
Author(s):  
Victoria (Shu) Zhang ◽  
Marissa D. King
Keyword(s):  
Longitudinal Data ◽  
Prescription Drug ◽  
Formation Processes ◽  
Prescribing Practices ◽  
Data Set ◽  
Substantial Body ◽  
Nuanced Understanding

Although a substantial body of work has investigated drivers of tie formation, there is growing interest in understanding why relationships decay or dissolve altogether. The networks literature has tended to conceptualize tie decay as driven by processes similar to those underlying tie formation. Yet information that is revealed through ongoing interactions can exert different effects on tie formation and tie decay. This paper investigates how tie decay and tie formation processes differ by focusing on contentious practices. To the extent that information about dissimilarities in contentious practices is learned through ongoing interactions, it can exert diverging effects on tie formation and tie decay. Using a longitudinal data set of 141,543 physician dyads, we find that differences in contentious prescribing led ties to weaken or dissolve altogether but did not affect tie formation. The more contentious the practice and the more information available about the practice, the stronger the effect on tie decay and dissolution. Collectively, these findings contribute to a more nuanced understanding of relationship evolution as an unfolding process through which deeper-level differences are revealed and shape the outcome of the tie.

scholarly journals A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement

2018 ◽  
Vol 2018 ◽  
pp. 1-42 ◽  
Author(s):  
Xiaomeng Shi ◽  
Zhirui Ye ◽  
Nirajan Shiwakoti ◽  
Offer Grembek
Keyword(s):  
Data Collection ◽  
Empirical Data ◽  
Empirical Studies ◽  
Movement Patterns ◽  
Simulation Models ◽  
Straight Line ◽  
Challenges And Opportunities ◽  
Pedestrian Traffic ◽  
Random Flows ◽  
Complex Movement

Complex movement patterns of pedestrian traffic, ranging from unidirectional to multidirectional flows, are frequently observed in major public infrastructure such as transport hubs. These multidirectional movements can result in increased number of conflicts, thereby influencing the mobility and safety of pedestrian facilities. Therefore, empirical data collection on pedestrians’ complex movement has been on the rise in the past two decades. Although there are several reviews of mathematical simulation models for pedestrian traffic in the existing literature, a detailed review examining the challenges and opportunities on empirical studies on the pedestrians complex movements is limited in the literature. The overall aim of this study is to present a systematic review on the empirical data collection for uni- and multidirectional crowd complex movements. We first categorized the complex movements of pedestrian crowd into two general categories, namely, external governed movements and internal driven movements based on the interactions with the infrastructure and among pedestrians, respectively. Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, diverging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, diverging, and random flows. We put emphasis on the need for the future global collaborative efforts on data sharing for the complex crowd movements.

scholarly journals High-resolution glacial and deglacial record of atmospheric methane by continuous-flow and laser spectrometer analysis along the NEEM ice core

2013 ◽  
Vol 9 (6) ◽  
pp. 2579-2593 ◽  
Author(s):  
J. Chappellaz ◽  
C. Stowasser ◽  
T. Blunier ◽  
D. Baslev-Clausen ◽  
E. J. Brook ◽  
...  
Keyword(s):  
High Resolution ◽  
Continuous Flow ◽  
Ice Core ◽  
Rate Of Change ◽  
Atmospheric Methane ◽  
Data Set ◽  
Rate Of Increase ◽  
Concentration Changes ◽  
Cross Dating ◽  
Laser Spectroscopic

Abstract. The Greenland NEEM (North Greenland Eemian Ice Drilling) operation in 2010 provided the first opportunity to combine trace-gas measurements by laser spectroscopic instruments and continuous-flow analysis along a freshly drilled ice core in a field-based setting. We present the resulting atmospheric methane (CH4) record covering the time period from 107.7 to 9.5 ka b2k (thousand years before 2000 AD). Companion discrete CH4 measurements are required to transfer the laser spectroscopic data from a relative to an absolute scale. However, even on a relative scale, the high-resolution CH4 data set significantly improves our knowledge of past atmospheric methane concentration changes. New significant sub-millennial-scale features appear during interstadials and stadials, generally associated with similar changes in water isotopic ratios of the ice, a proxy for local temperature. In addition to the midpoint of Dansgaard–Oeschger (D/O) CH4 transitions usually used for cross-dating, sharp definition of the start and end of these events brings precise depth markers (with ±20 cm uncertainty) for further cross-dating with other palaeo- or ice core records, e.g. speleothems. The method also provides an estimate of CH4 rates of change. The onsets of D/O events in the methane signal show a more rapid rate of change than their endings. The rate of CH4 increase associated with the onsets of D/O events progressively declines from 1.7 to 0.6 ppbv yr−1 in the course of marine isotope stage 3. The largest observed rate of increase takes place at the onset of D/O event #21 and reaches 2.5 ppbv yr−1.

Acetyl L-Carnitine Slows Decline in Younger Patients With Alzheimer's Disease: A Reanalysis of a Double-Blind, Placebo-Controlled Study Using the Trilinear Approach

1998 ◽  
Vol 10 (2) ◽  
pp. 193-203 ◽  
Author(s):  
John O. Brooks ◽  
Jerome A. Yesavage ◽  
Angelico Carta ◽  
Daniele Bravi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Average Rate ◽  
The United States ◽  
Rate Of Change ◽  
Disease Assessment ◽  
Controlled Study ◽  
Double Blind ◽  
Parallel Group ◽  
Longitudinal Effects

Objectives: To assess the longitudinal effects of acetyl-L-carnitine (ALC) on patients diagnosed with Alzheimer's disease. Design: Longitudinal, double-blind, parallel-group, placebocontrolled. Setting: Twenty-four outpatient sites across the United States. Participants: A total of 334 subjects diagnosed with probable Alzheimer's disease by NINCDS-ADRDA criteria. These data were originally reported by Thal and colleagues (1996). Measurements: Cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS) given every 3 months for 1 year. Results: The average rate of change was estimated using the trilinear approach, which allows for periods of both change and stability. Both the ALC group and the placebo group exhibited the same mean rate of change on the ADAS (0.68 points/month). However, a multiple regression analysis revealed a statistically significant Age × Drug interaction characterized by younger subjects benefiting more from ALC treatment than older subjects. Further analyses suggested that the optimal, though not statistically significant, cutpoint for ALC benefit was 61 years of age. Conclusions: ALC slows the progression of Alzheimer's disease in younger subjects, and the use of the trilinear approach to estimate the average rate of change may prove valuable in pharmacological trials.

Sexism and Gender Inequality Across 57 Societies

2011 ◽  
Vol 22 (11) ◽  
pp. 1413-1418 ◽  
Author(s):  
Mark J. Brandt
Keyword(s):  
Longitudinal Data ◽  
Multilevel Modeling ◽  
Gender Inequality ◽  
Past Research ◽  
Status Quo ◽  
Data Set ◽  
Representative Data ◽  
Gender Hierarchy ◽  
And Gender

Theory predicts that individuals’ sexism serves to exacerbate inequality in their society’s gender hierarchy. Past research, however, has provided only correlational evidence to support this hypothesis. In this study, I analyzed a large longitudinal data set that included representative data from 57 societies. Multilevel modeling showed that sexism directly predicted increases in gender inequality. This study provides the first evidence that sexist ideologies can create gender inequality within societies, and this finding suggests that sexism not only legitimizes the societal status quo, but also actively enhances the severity of the gender hierarchy. Three potential mechanisms for this effect are discussed briefly.

scholarly journals Comparison of Deep Neural Network Models and Effectiveness of EMG Signal Feature Value for Estimating Dorsiflexion

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2767
Author(s):  
Muhammad Akmal Bin Mohammed Zaffir ◽  
Praveen Nuwantha ◽  
Daiki Arase ◽  
Keiko Sakurai ◽  
Hiroki Tamura
Keyword(s):  
Neural Network ◽  
Average Rate ◽  
Network Models ◽  
Rate Of Change ◽  
Estimation Accuracy ◽  
Neural Network Models ◽  
Emg Signal ◽  
Minimum Number ◽  
Deep Learning Network ◽  
Simple Network

(1) Background: Robotic ankle–foot orthoses (AFO) are often used for gait rehabilitation. Our research focuses on the design and development of a robotic AFO with minimum number of sensor inputs. However, this leads to degradation of gait estimation accuracy. (2) Methods: To prevent degradation of accuracy, we compared a few neural network models in order to determine the best network when only two input channels are being used. Further, the EMG signal feature value of average rate of change was used as input. (3) Results: LSTM showed the highest accuracy. However, MLP with a small number of hidden layers showed results similar to LSTM. Moreover, the accuracy for all models, with the exception of LSTM for one subject (SD), increased with the addition of feature value (average rate of change) as input. (4) Conclusions: In conclusion, time-series networks work best with a small number of sensor inputs. However, depending on the optimizer being used, even a simple network can outrun a deep learning network. Furthermore, our results show that applying EMG signal feature value as an input tends to increase the estimation accuracy of the network.

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 Use of Magnetic Field for Mitigating Gyroscope Errors for Indoor Pedestrian Positioning

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2592 ◽  
Author(s):  
Ming Ma ◽  
Qian Song ◽  
Yang Gu ◽  
Zhimin Zhou
Keyword(s):  
Magnetic Field ◽  
Static Magnetic Field ◽  
Inertial Navigation System ◽  
Three Dimensional ◽  
Calibration Method ◽  
Rate Of Change ◽  
Superior Performance ◽  
Novel Approach ◽  
Straight Line ◽  
Magnetometer Calibration

In the field of indoor pedestrian positioning, the improved Quasi-Static magnetic Field (iQSF) method has been proposed to estimate gyroscope biases in magnetically perturbed environments. However, this method is only effective when a person walks along straight-line paths. For other curved or more complex path patterns, the iQSF method would fail to detect the quasi-static magnetic field. To address this issue, a novel approach is developed for quasi-static magnetic field detection in foot-mounted Inertial Navigation System. The proposed method detects the quasi-static magnetic field using the rate of change in differences between the magnetically derived heading and the heading derived from gyroscope. In addition, to eliminate the distortions caused by system platforms and shoes, a magnetometer calibration method is developed and the calibration is transformed from three-dimensional to two-dimensional coordinate according to the motion model of a pedestrian. The experimental results demonstrate that the proposed method can provide superior performance in suppressing the heading errors with the comparison to iQSF method.

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