Subject Selection Bias in Intervention Experiments with Socially Assistive Robots and the Impact on the Representativeness of the Population

Author(s):  
Toshiharu Igarashi ◽  
Misato Nihei ◽  
Jumpei Mizuno ◽  
Takenobu Inoue ◽  
Minoru Kamata
2019 ◽  
Vol 81 (1-2) ◽  
pp. 81-86
Author(s):  
Pierre Koskas ◽  
Mouna Romdhani ◽  
Olivier Drunat

As commonly happens in epidemiological research, none of the reported studies were totally free of methodological problems. Studies have considered the influence of social relationships on dementia, but the mechanisms underlying these associations are not perfectly understood. We look at the possible impact of selection bias. For their first memory consultation, patients may come alone or accompanied by a relative. Our objective is to better understand the impact of this factor by retrospective follow-up of geriatric memory outpatients over several years. All patients over 70 who were referred to Bretonneau Memory Clinic for the first time, between January 2006 and 2018, were included in the study. The patients who came alone formed group 1, the others, whatever type of relative accompanied them, formed group 2. We compared the Mini-Mental State Examination (MMSE) scores of patients; and for all patients who came twice for consultation with at least a 60-day interval, we compared their first MMSE with the MMSE performed at the second consultation. In total, 2,935 patients were included, aged 79.7 ± 8.4 years. Six hundred and twenty-five formed group 1 and 2,310 group 2. We found a significant difference in MMSE scores between the 2 groups of patients; and upon second consultation in group 2, but that difference was minor in group 1. Our finding of a possible confounding factor underlines the complexity of choosing comparison groups in order to minimize selection bias while maintaining clinical relevance.


2016 ◽  
Vol 29 (3) ◽  
pp. 313-331 ◽  
Author(s):  
Grant Richardson ◽  
Grantley Taylor ◽  
Roman Lanis

Purpose This paper aims to investigate the impact of women on the board of directors on corporate tax avoidance in Australia. Design/methodology/approach The authors use multivariate regression analysis to test the association between the presence of female directors on the board and tax aggressiveness. They also test for self-selection bias in the regression model by using the two-stage Heckman procedure. Findings This paper finds that relative to there being one female board member, high (i.e. greater than one member) female presence on the board of directors reduces the likelihood of tax aggressiveness. The results are robust after controlling for self-selection bias and using several alternative measures of tax aggressiveness. Research limitations/implications This study extends the extant literature on corporate governance and tax aggressiveness. This study is subject to several caveats. First, the sample is restricted to publicly listed Australian firms. Second, this study only examines the issue of women on the board of directors and tax aggressiveness in the context of Australia. Practical implications This research is timely, as there has been increased pressure by government bodies in Australia and globally to develop policies to increase female representation on the board of directors. Originality/value This study is the first to provide empirical evidence concerning the association between the presence of women on the board of directors and tax aggressiveness.


AI Magazine ◽  
2015 ◽  
Vol 36 (4) ◽  
pp. 23-33 ◽  
Author(s):  
Domen Novak ◽  
Robert Riener

Rehabilitation robots physically support and guide a patient's limb during motor therapy, but require sophisticated control algorithms and artificial intelligence to do so. This article provides an overview of the state of the art in this area. It begins with the dominant paradigm of assistive control, from impedance-based cooperative controller through electromyography and intention estimation. It then covers challenge-based algorithms, which provide more difficult and complex tasks for the patient to perform through resistive control and error augmentation. Furthermore, it describes exercise adaptation algorithms that change the overall exercise intensity based on the patient's performance or physiological responses, as well as socially assistive robots that provide only verbal and visual guidance. The article concludes with a discussion of the current challenges in rehabilitation robot software: evaluating existing control strategies in a clinical setting as well as increasing the robot's autonomy using entirely new artificial intelligence techniques.


1993 ◽  
Vol 72 (2) ◽  
pp. 223-225 ◽  
Author(s):  
David M. Salerno ◽  
Kyuhyun Wang ◽  
Irvin F. Goldenberg ◽  
Robert A. Van Tassel

2009 ◽  
Vol 19 (1) ◽  
pp. 33-41.e1 ◽  
Author(s):  
Martine Vrijheid ◽  
Lesley Richardson ◽  
Bruce K. Armstrong ◽  
Anssi Auvinen ◽  
Gabriele Berg ◽  
...  

2021 ◽  
Author(s):  
Brad McKay ◽  
Zachary Yantha ◽  
Julia Hussien ◽  
Michael J Carter ◽  
Diane M. Ste-Marie

The self-controlled motor learning literature consists of experiments that compare a group of learners who are provided with a choice over an aspect of their practice environment to a group who are yoked to those choices. A qualitative review of the literature suggests an unambiguous benefit from self-controlled practice. A meta-analysis was conducted on the effects of self-controlled practice on retention test performance measures with a focus on assessing and potentially correcting for selection bias in the literature, such as publication bias and p-hacking. First, a naïve random effects model was fit to the data and a moderate benefit of self-controlled practice, g=.44 (k= 52,N= 3134,95%CI[.31, .56]), was found. Second, publication status was added to the model as a potential moderator, revealing a significant difference between published and unpublished findings, with only the former reporting a benefit of self-controlled practice. Third, to investigate and adjust for the impact of selectively reporting statistically significant results, a weight-function model was fit to the data with a one-tailed p-value cutpoint of .025. The weight-function model revealed substantial selection bias and estimated the true average effect of self-controlled practice as g=.107 (95%CI[.047, .18]). P-curve analyses were conducted on the statistically significant results published in the literature and the outcome suggested a lack of evidential value. Fourth, a suite of sensitivity analyses were conducted to evaluate the robustness of these results, all of which converged on trivially small effect estimates. Overall, our results suggest the benefit of self-controlled practice on motor learning is small and not currently distinguishable from zero.


2012 ◽  
Vol 13 (2) ◽  
pp. 114-120.e1 ◽  
Author(s):  
Roger Bemelmans ◽  
Gert Jan Gelderblom ◽  
Pieter Jonker ◽  
Luc de Witte

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