scholarly journals A data-driven approach to monitoring data collection in an online panel

2019 ◽  
Vol 10 (4) ◽  
pp. 433-452
Author(s):  
Jessica M.E. Herzing ◽  
Caroline Vandenplas ◽  
Julian B. Axenfeld
Keyword(s):  
Data Collection ◽  
Multilevel Models ◽  
Data Driven ◽  
Response Proportion ◽  
Panel Surveys ◽  
Online Panel ◽  
Response Enhancement ◽  
Daily Response ◽  
Data Driven Approach ◽  
Collection Phase

Longitudinal or panel surveys suffer from panel attrition which may result in biased estimates. Online panels are no exceptions to this phenomenon, but offer great possibilities in monitoring and managing the data-collection phase and response-enhancement features (such as reminders), due to real-time availability of paradata. This paper presents a data-driven approach to monitor the data-collection phase and to inform the adjustment of response-enhancement features during data collection across online panel waves, which takes into account the characteristics of an ongoing panel wave. For this purpose, we study the evolution of the daily response proportion in each wave of a probability-based online panel. Using multilevel models, we predict the data-collection evolution per wave day. In our example, the functional form of the data-collection evolution is quintic. The characteristics affecting the shape of the data-collection evolution are those of the specific wave day and not of the panel wave itself. In addition, we simulate the monitoring of the daily response proportion of one panel wave and find that the timing of sending reminders could be adjusted after 20 consecutive panel waves to keep the data-collection phase efficient. Our results demonstrate the importance of re-evaluating the characteristics of the data-collection phase, such as the timing of reminders, across the lifetime of an online panel to keep the fieldwork efficient.

Automation and the Human Factors Race to Catch Up

2017 ◽  
Vol 12 (1) ◽  
pp. 83-85 ◽  
Author(s):  
Catherine M. Burns
Keyword(s):  
Data Collection ◽  
Human Factors ◽  
Technological Change ◽  
Data Driven ◽  
Massive Data ◽  
Laboratory Studies ◽  
Data Driven Approach ◽  
Catch Up

Automation has been rapidly developing into a pervasive part of our every day lives. Although I agree with Kaber’s original article, I argue that human factors as a discipline is not keeping up with the pace of technological change. Human factors researchers must rapidly embrace the development of richer automation models, more complex laboratory studies, and naturalistic studies in the field to generate relevant insights into human automation interaction. The corresponding development of massive data collection presents an opportunity for a more data-driven approach to understanding human automation interaction and human factors in general.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

2012 ◽  
Author(s):  
Michael Ghil ◽  
Mickael D. Chekroun ◽  
Dmitri Kondrashov ◽  
Michael K. Tippett ◽  
Andrew Robertson ◽  
...  
Keyword(s):  
Dynamic Models ◽  
Data Driven ◽  
Stochastic Dynamic ◽  
Extended Range ◽  
Data Driven Approach ◽  
Low Dimensional

A Mostly Data-Driven Approach to Inverse Text Normalization

2017 ◽  
Author(s):  
Ernest Pusateri ◽  
Bharat Ram Ambati ◽  
Elizabeth Brooks ◽  
Ondrej Platek ◽  
Donald McAllaster ◽  
...  
Keyword(s):  
Data Driven ◽  
Data Driven Approach ◽  
Text Normalization

Ethics in Social Research

2018 ◽  
Author(s):  
Steve Bruce
Keyword(s):  
Informed Consent ◽  
Data Collection ◽  
Research Ethics ◽  
Social Research ◽  
Medical Interventions ◽  
Ethical Implications ◽  
Social Researcher ◽  
Naturally Occurring ◽  
The Social ◽  
Collection Phase

It is right that social researchers consider the ethical implications of their work, but discussion of research ethics has been distorted by the primacy of the ‘informed consent’ model for policing medical interventions. It is remarkably rare for the data collection phase of social research to be in any sense harmful, and in most cases seeking consent from, say, members of a church congregation would disrupt the naturally occurring phenomena we wish to study. More relevant is the way we report our research. It is in the disparity between how people would like to see themselves described and explained and how the social researcher describes and explains them that we find the greatest potential for ill-feeling, and even here it is slight.

scholarly journals Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1571 ◽  
Author(s):  
Jhonatan Camacho Navarro ◽  
Magda Ruiz ◽  
Rodolfo Villamizar ◽  
Luis Mujica ◽  
Jabid Quiroga
Keyword(s):  
Correlation Analysis ◽  
Damage Assessment ◽  
Structural Damage ◽  
Cross Correlation ◽  
Data Driven ◽  
Cross Correlation Analysis ◽  
Data Driven Approach
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