scholarly journals Mode Effects in Mixed-Mode Economic Surveys: Insights from a Randomized Experiment

2015 ◽  
Author(s):  
Joanne W. Hsu ◽  
Brooke Helppie McFall
Keyword(s):  
Mixed Mode ◽  
Randomized Experiment ◽  
Mode Effects

scholarly journals A three-dimensional elastoplastic analysis of mixed-mode KI/KII around the crack front

2019 ◽  
Vol 300 ◽  
pp. 11002
Author(s):  
Luiz Fernando Nazaré Marques ◽  
Jaime Tupiassú Pinho de Castro ◽  
Luiz Fernando Martha ◽  
Marco Antonio Meggiolaro
Keyword(s):  
Crack Front ◽  
Mixed Mode ◽  
Three Dimensional ◽  
Local Stress ◽  
Mode I ◽  
Pure Mode ◽  
Mode Effects ◽  
Fatigue And Fracture ◽  
Edge Tension ◽  
Combined Mode

Engineering problems that involve fatigue crack growth and fracture frequently can be studied by taking into account only mode-I features. However, many important problems that involve combined mode I and II loadings cannot be properly analyzed by a pure mode-I approach, which in particular may not be sufficient to estimate fracture toughness for practical purposes in such cases. Such mixed-mode problems involve crack orientation and/or load conditions that lead to combined local Stress Intensity Factors (SIFs) KI/KII around the crack front. Using multiaxial crack tip condition characterized by the crack inclination angle βin a mixed-mode KI/KII modified single edge tension SE(T) specimen, such mixed-mode effects on plastic zone shapes, volumes and plastic work UPL are taken into account to evaluate problems that involve fatigue and fracture.

scholarly journals Mode effects in concurrent mixed-mode surveys

2016 ◽  
Vol 29 (5) ◽  
pp. 787-806
Author(s):  
Jeeseon Baek ◽  
Kyung A Min
Keyword(s):  
Mixed Mode ◽  
Mode Effects

Modelling Mode Effects for a Panel Survey in Transition

2021 ◽  
pp. 63-88
Author(s):  
Paul P. Biemer ◽  
Kathleen Mullan Harris ◽  
Dan Liao ◽  
Brian J. Burke ◽  
Carolyn Tucker Halpern
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Mixed Mode ◽  
Good News ◽  
Longitudinal Change ◽  
Nonresponse Bias ◽  
Two Phase ◽  
Mode Effects ◽  
Analytical Results ◽  
Weighting Adjustments

Funding reductions combined with increasing data-collection costs required that Wave V of the USA’s National Longitudinal Study of Adolescent to Adult Health (Add Health) abandon its traditional approach of in-person interviewing and adopt a more cost-effective method. This approach used the mail/web mode in Phase 1 of data collection and in-person interviewing for a random sample of nonrespondents in Phase 2. In addition, to facilitate the comparison of modes, a small random subsample served as the control and received the traditional in-person interview. We show that concerns about reduced data quality as a result of the redesign effort were unfounded based on findings from an analysis of the survey data. In several important respects, the new two-phase, mixed-mode design outperformed the traditional design with greater measurement accuracy, improved weighting adjustments for mitigating the risk of nonresponse bias, reduced residual (or post-adjustment) nonresponse bias, and substantially reduced total-mean-squared error of the estimates. This good news was largely unexpected based upon the preponderance of literature suggesting data quality could be adversely affected by the transition to a mixed mode. The bad news is that the transition comes with a high risk of mode effects for comparing Wave V and prior wave estimates. Analytical results suggest that significant differences can occur in longitudinal change estimates about 60 % of the time purely as an artifact of the redesign. This begs the question: how, then, should a data analyst interpret significant findings in a longitudinal analysis in the presence of mode effects? This chapter presents the analytical results and attempts to address this question.

Making Mobile Browser Surveys Smarter

Field Methods ◽  
2014 ◽  
Vol 26 (4) ◽  
pp. 322-342 ◽  
Author(s):  
Trent D. Buskirk ◽  
Charles H. Andrus
Keyword(s):  
Randomized Experiment ◽  
Block Group ◽  
Data Collection Tool ◽  
Laptop Computer ◽  
Web Browser ◽  
Survey Mode ◽  
Mode Effects ◽  
Missing Item ◽  
Completion Times ◽  
Process Completion

With nearly 50% of U.S. mobile phone subscribers using smartphones, survey researchers are beginning to explore their use as a data collection tool. The Got Healthy Apps Study (GHAS) conducted a randomized experiment to compare mode effects for a survey completed via iPhone mobile browser and online via desktop/laptop computer web browser. Mode effects were assessed for three types of outcomes: randomization/recruitment, survey process/completion, and survey items. In short, the distribution of survey completion times and the distribution of the number of apps owned were significantly different across survey mode after accounting for block group. Other key mode effects outcomes (including open-ended items, slider bar questions, and missing item rates) showed no significant differences across survey mode. Some interesting qualitative findings suggest that iPhone respondents enter more characters and omit fewer items than originally thought.

scholarly journals Mode Effects on Data Quality and Measurement in a Mixed-Mode Time-Use Survey

2021 ◽  
Author(s):  
Stella Chatzitheochari ◽  
Elena Mylona
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Time Use ◽  
Mixed Mode ◽  
Large Scale ◽  
New Technologies ◽  
Quality Data ◽  
Mode Effects ◽  
Time Use Survey ◽  
Time Diaries

Recent years have witnessed an increasing interest in the use of new technologies for time-use data collection, driven by their potential to reduce survey administration costs and improve data quality. However, despite the steady growth of studies that employ web and app time diaries, there is little research on their comparability with traditional paper-administered diaries that have long been regarded as the “gold standard” for measurement in time-use research. This paper rectifies this omission by investigating diary mode effects on data quality and measurement, drawing on data from a mixed-mode large-scale time diary study of adolescents in the United Kingdom. After controlling for selection effects, we find that web and app diaries yield higher quality data than paper diaries, which attests to the potential of new technologies in facilitating diary completion. At the same time, our analysis of broad time-use domains does not find substantial mode effects on measurement for the majority of daily activity categories. We conclude by discussing avenues for future methodological research and implications for time-use data collection.

scholarly journals A Method for Evaluating Mode Effects in Mixed-mode Surveys

2010 ◽  
Vol 74 (5) ◽  
pp. 1027-1045 ◽  
Author(s):  
J. Vannieuwenhuyze ◽  
G. Loosveldt ◽  
G. Molenberghs
Keyword(s):  
Mixed Mode ◽  
Mode Effects
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