Individual patient- versus group-level data meta-regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head

2002 ◽  
Vol 21 (3) ◽  
pp. 371-387 ◽  
Author(s):  
Jesse A. Berlin ◽  
Jill Santanna ◽  
Christopher H. Schmid ◽  
Lynda A. Szczech ◽  
Harold I. Feldman ◽  
...  
Keyword(s):  
Treatment Effect ◽  
Group Level ◽  
Versus Group ◽  
Ecological Bias ◽  
Level Data

Organization Versus Group-Level Safety Climate Perceptions: Association With Safety Behavior and Outcome

2013 ◽  
Author(s):  
Yueng-Hsiang Huang ◽  
Dov Zohar ◽  
Michelle Robertson ◽  
Jin Lee ◽  
Jenn Rineer ◽  
...  
Keyword(s):  
Safety Climate ◽  
Group Level ◽  
Safety Behavior ◽  
Versus Group ◽  
Climate Perceptions

scholarly journals The closer to the Europe Union headquarters, the higher risk of COVID-19? Cautions regarding ecological studies of COVID-19

2020 ◽  
Author(s):  
Shuai Li ◽  
Xinyang Hua
Keyword(s):  
European Country ◽  
Ecological Study ◽  
Ecological Fallacy ◽  
Group Level ◽  
Ecological Studies ◽  
Public Concern ◽  
Individual Level ◽  
The Public ◽  
Country Level ◽  
Level Data

AbstractSeveral ecological studies of the coronavirus disease 2019 (COVID-19) have reported correlations between group-level aggregated exposures and COVID-19 outcomes. While some studies might be helpful in generating new hypotheses related to COVID-19, results of such type of studies should be interpreted with cautions. To illustrate how ecological studies and results could be biased, we conducted an ecological study of COVID-19 outcomes and the distance to Brussels using European country-level data. We found that, the distance was negatively correlated with COVID-19 outcomes; every 100 km away from Brussels was associated with approximately 6% to 17% reductions (all P<0.01) in COVID-19 cases and deaths in Europe. Without cautions, such results could be interpreted as the closer to the Europe Union headquarters, the higher risk of COVID-19 in Europe. However, these results are more likely to reflect the differences in the timing of and the responding to the outbreak, etc. between European countries, rather than the ‘effect’ of the distance to Brussels itself. Associations observed at the group level have limitations to reflect individual-level associations – the so-called ecological fallacy. Given the public concern over COVID-19, ecological studies should be conducted and interpreted with great cautions, in case the results would be mistakenly understood.

scholarly journals Aging and efficacy of disease-modifying therapies in multiple sclerosis: a meta-analysis of clinical trials

2020 ◽  
Vol 13 ◽  
pp. 175628642096901
Author(s):  
Yinan Zhang ◽  
Natalia Gonzalez Caldito ◽  
Afsaneh Shirani ◽  
Amber Salter ◽  
Gary Cutter ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Disease Activity ◽  
Meta Analysis ◽  
Group Level ◽  
T2 Lesions ◽  
Disease Modifying Therapies ◽  
Level Data ◽  
Disease Modifying ◽  
Magnetic Resonance Imaging Mri

Background: Disease-modifying therapies (DMTs) for multiple sclerosis (MS) are approved for the treatment of disease activity and are effective in reducing relapses and new magnetic resonance imaging (MRI) lesions. However, disease activity generally subsides with time, and age-dependent changes in DMT efficacy are not well-established. We aimed to investigate whether age impacts the efficacy of DMTs in treating disease activity in patients with relapsing–remitting MS (RRMS). Methods: DMT efficacy related to age was assessed through a meta-analysis of clinical trials that evaluated the efficacy of DMTs in RRMS patients as measured by reductions in the annualized relapse rate (ARR), new T2 lesions, and gadolinium-enhanced lesions on MRI. Using the mean baseline patient age from each trial, a weighted linear regression was fitted to determine whether age was associated with treatment efficacy on a group level. Results: Group-level data from a total of 28,082 patients from 26 trials of 14 different DMTs were included in the meta-analysis. There were no statistically significant associations between age and reductions in ARR, new T2 lesions, and gadolinium-enhanced lesions of the treatment group compared with placebo. Conclusion: DMTs for RRMS show efficacy in treating disease activity independent of age as demonstrated by group-level data from DMT clinical trials. Nevertheless, clinical trials select for patients with baseline disease activity regardless of age, thereby not representing real-world patients with RRMS, where disease activity declines with age.

Decrement and the Illusions of the Mueller-Lyer Figure

1994 ◽  
Vol 79 (2) ◽  
pp. 707-717 ◽  
Author(s):  
Clare Porac
Keyword(s):  
Perceptual Learning ◽  
Illusion Magnitude ◽  
Group Level ◽  
Illusion Decrement ◽  
Significant Time ◽  
Lyer Illusion ◽  
Significant Decrement ◽  
Level Data

Decrement, a time-related decrease in the magnitude of the Mueller-Lyer illusion, was measured separately for the wings-out and the wings-in variants of the Mueller-Lyer figure. There were significant reductions of wings-out illusion magnitude during the decrement period. Observers viewing the wings-in segment showed a non-significant decrement pattern. Analyses of individual decrement patterns showed that illusion magnitude did not decrease for a number of observers even when there were significant time-related trends at the group level. Data for 80 observers imply that the mechanisms of perceptual learning proposed by previous models of Mueller-Lyer illusion decrement are not sufficient explanations of the decrement process.

Partitioning Ethnic Groups and their Members: Explaining Variations in Satisfaction with Democracy in Africa

2012 ◽  
Vol 18 (3) ◽  
Author(s):  
Valentin Gold
Keyword(s):  
Comparative Analysis ◽  
Ethnic Group ◽  
Ethnic Groups ◽  
Multilevel Model ◽  
National Level ◽  
National Context ◽  
Group Level ◽  
Satisfaction With Democracy ◽  
Level Data ◽  
Over Time

AbstractThis article examines the conditions that influence citizens’ satisfaction with democracy in Africa. In the analysis, individual, ethnic group, and national context determinants are combined in a multilevel model allowing a comparative analysis over time, countries, ethnic groups, and individuals. Using Afrobarometer survey data along with ethnic group-level and national-level data, I show that factors shaping citizens’ satisfaction can be found on each contextual level. To a large extent, perceived economic and political inequalities between ethnic groups explain variations in citizens’ satisfaction.

scholarly journals Tax Law Asymmetries and Income Shifting: Evidence from Japanese Capital Keiretsu

2010 ◽  
Vol 10 (1) ◽  
Author(s):  
Kazuki Onji ◽  
David Vera
Keyword(s):  
Tax Incentives ◽  
Attrition Rate ◽  
Income Shifting ◽  
Tax Law ◽  
Group Level ◽  
Large Dataset ◽  
Corporate Groups ◽  
Negative Income ◽  
Level Data ◽  
The Impact

Abstract While the asymmetric treatment of positive and negative income creates clear tax incentives to shift income among a group of closely related corporations, attempts to document the impact of such behavior on economic outcomes are relatively sparse. We aim to provide evidence on tax-motivated transfers from a large dataset of Japanese corporate groups. Using company level data on 33,340 subsidiary time pairs from 1988, 1990, and 1992, we consider testable implications of income shifting in a theoretical model tailored to the Japanese institution of the early 1990s and empirically examine the spread of the profitability distribution, the attrition rate of loss-making subsidiaries, and the propensity to report zero profit. The findings suggest that income shifting was pervasive when Japan had not adopted a formal allowance for group-level tax. The result underscores the importance of accounting for the inter-relatedness of companies, in designing a corporate income tax.

scholarly journals Doing nothing and what it looks like: inactivity in fattening cattle

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9395
Author(s):  
Sara Hintze ◽  
Freija Maulbetsch ◽  
Lucy Asher ◽  
Christoph Winckler
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Statistical Hypothesis ◽  
Machine Learning Algorithm ◽  
Body Parts ◽  
Group Level ◽  
Statistical Hypothesis Testing ◽  
Level Data ◽  
Eyes Open ◽  
Husbandry System

Background Animals kept in barren environments often show increased levels of inactivity and first studies indicate that inactive behaviour may reflect boredom or depression-like states. However, to date, knowledge of what inactivity looks like in different species is scarce and methods to precisely describe and analyse inactive behaviour are thus warranted. Methods We developed an Inactivity Ethogram including detailed information on the postures of different body parts (Standing/Lying, Head, Ears, Eyes, Tail) for fattening cattle, a farm animal category often kept in barren environments. The Inactivity Ethogram was applied to Austrian Fleckvieh heifers kept in intensive, semi-intensive and pasture-based husbandry systems to record inactive behaviour in a range of different contexts. Three farms per husbandry system were visited twice; once in the morning and once in the afternoon to cover most of the daylight hours. During each visit, 16 focal animals were continuously observed for 15 minutes each (96 heifers per husbandry system, 288 in total). Moreover, the focal animals’ groups were video recorded to later determine inactivity on the group level. Since our study was explorative in nature, we refrained from statistical hypothesis testing, but analysed both the individual- and group-level data descriptively. Moreover, simultaneous occurrences of postures of different body parts (Standing/Lying, Head, Ears and Eyes) were analysed using the machine learning algorithm cspade to provide insight into co-occurring postures of inactivity. Results Inspection of graphs indicated that with increasing intensity of the husbandry system, more animals were inactive (group-level data) and the time the focal animals were inactive increased (individual-level data). Frequently co-occurring postures were generally similar between husbandry systems, but with subtle differences. The most frequently observed combination on farms with intensive and semi-intensive systems was lying with head up, ears backwards and eyes open whereas on pasture it was standing with head up, ears forwards and eyes open. Conclusion Our study is the first to explore inactive behaviour in cattle by applying a detailed description of postures from an Inactivity Ethogram and by using the machine learning algorithm cspade to identify frequently co-occurring posture combinations. Both the ethogram created in this study and the cspade algorithm may be valuable tools in future studies aiming to better understand different forms of inactivity and how they are associated with different affective states.

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