Deprived People or Deprived Places? Exploring the Ecological Fallacy in Studies of Deprivation with the Samples of Anonymised Records

1996 ◽  
Vol 28 (2) ◽  
pp. 237-259 ◽  
Author(s):  
E A Fieldhouse ◽  
R Tye
Keyword(s):  
Specific Problem ◽  
Ecological Fallacy ◽  
Demographic Groups ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Small Area Statistics ◽  
Equivalent Area ◽  
Social Demographic ◽  
Local Base

In recent years have seen an increase in the analysis of deprivation in Britain. In most studies the unit of analysis has been geographical, such as local-government wards or districts. This reflects, in part, a reliance on small-area statistics and local-base statistics from the censuses of population. Although useful in identifying specific problem areas, this type of approach may be subject to ecological fallacy. In other words, areas of high levels of deprivation may be home to high proportions of particular social or demographic groups, but it cannot be automatically assumed that these groups are themselves deprived. Although some studies have been based on purpose-designed individual-level survey data, these often lack sufficient sample sizes to analyse effectively small subgroups of the population or to allow geographical disaggregation. The release of the Samples of Anonymised Records from the 1991 Census allows individual-level data to be used to investigate the social, demographic, and geographical dimensions of deprivation. In this paper, a threshold of deprivation will be determined and the distribution of individual-level deprivation (deprived people) will be compared with an equivalent area-level index constructed from standard census output by the use of conventional techniques.

Antecedents of growth-oriented entrepreneurship before and during the Greek economic crisis

2017 ◽  
Vol 24 (3) ◽  
pp. 528-544 ◽  
Author(s):  
Ioannis Giotopoulos ◽  
Alexandra Kontolaimou ◽  
Aggelos Tsakanikas
Keyword(s):  
Work Experience ◽  
Early Stage ◽  
New Ventures ◽  
High Growth ◽  
Content Type ◽  
Crisis Period ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Before And After

Purpose The purpose of this paper is to explore potential drivers of high-growth intentions of early-stage entrepreneurs in Greece before and after the onset of the financial crisis of 2008. Design/methodology/approach To this end, the authors use individual-level data retrieved from Global Entrepreneurship Monitor annual surveys (2003-2015). Findings The results show that high-growth intentions of Greek entrepreneurs are driven by different factors in the crisis compared to the non-crisis period. Male entrepreneurs and entrepreneurs with significant work experience seem to be more likely to be engaged in growth-oriented new ventures during the crisis period. The same appears to hold for entrepreneurs who are motivated by an opportunity and also perceive future business opportunities in adverse economic conditions. On the other hand, the educational level and the social contacts of founders with other entrepreneurs are found to drive ambitious Greek entrepreneurship in the years before the crisis, while they were insignificant after the crisis outbreak. Originality/value Based on the concept of ambitious entrepreneurship, this study contributes to the literature by investigating the determinants of entrepreneurial high-growth expectations in the Greek context emphasizing the crisis period in comparison to the pre-crisis years.

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.

Medicare and Medicaid Services Online

2015 ◽  
pp. 696-710
Author(s):  
Mary Schmeida ◽  
Ramona McNeal
Keyword(s):  
Health Insurance ◽  
Multivariate Regression Analysis ◽  
The United States ◽  
Vulnerable Groups ◽  
Government Programs ◽  
Life Project ◽  
Demographic Groups ◽  
Individual Level ◽  
Level Data ◽  
Access To Health

Government initiatives in the United States have been passed in an effort to increase citizen usage of e-government programs. One such service is the availability of online health insurance information. However, not all demographic groups have been equally able to access these services, primarily the poor and rural American. As more legislation is passed, including the advancement of broadband services to remote areas, infrastructure barriers are being removed, opening access to Medicare and Medicaid websites for these vulnerable groups. The purpose of this chapter is to analyze factors predicting the impact of recent government actions on citizen access to health insurance information online. This topic is explored using multivariate regression analysis and individual level data from the Internet and American Life Project. The findings suggest that healthcare needs and quality of Internet access may be playing a more important role in health insurance information services than other factors.

scholarly journals The inequity of morbidity: Disparities in the prevalence of morbidity between ethnic groups in New Zealand

2020 ◽  
Vol 10 ◽  
pp. 2235042X2097116
Author(s):  
Jason Gurney ◽  
James Stanley ◽  
Diana Sarfati
Keyword(s):  
New Zealand ◽  
Ethnic Groups ◽  
Latin American ◽  
Middle Eastern ◽  
National Level ◽  
Morbidity Burden ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
The Impact

Objective: The burden of chronic disease is not evenly shared within our society. In this manuscript, we use comprehensive national-level data to compare morbidity burden between ethnic groups in New Zealand. Methods: We investigated the prevalence of morbidity among all New Zealanders aged 18+ (n = 3,296,837), stratified by ethnic group (Māori, Pacific, Asian, Middle Eastern/Latin American/African, European/Other), using national-level hospitalisation and pharmaceutical data and two measures of morbidity (the M3 and P3 indices). Results and Conclusions: We observed substantial disparities for Māori and Pacific peoples compared to other ethnic groups for the vast majority of commonly-diagnosed morbidities. These disparities appeared strongest for the most-common conditions – meaning that Māori and Pacific peoples disproportionately shoulder an increased burden of these key conditions. We also observed that prevalence of these conditions emerged at earlier ages, meaning that Māori and Pacific peoples also experience a disproportionate impact of individual conditions on the quality and quantity of life. Finally, we observed strong disparities in the prevalence of conditions that may exacerbate the impact of COVID-19, such as chronic pulmonary, liver or renal disease. The substantial inequities we have presented here have been created and perpetuated by the social determinants of health, including institutionalised racism: thus solutions will require addressing these systemic issues as well as addressing inequities in individual-level care.

scholarly journals Invited Commentary: Making Causal Inference More Social and (Social) Epidemiology More Causal

2019 ◽  
Vol 189 (3) ◽  
pp. 179-182
Author(s):  
John W Jackson ◽  
Onyebuchi A Arah
Keyword(s):  
Causal Inference ◽  
Causal Reasoning ◽  
Social Epidemiology ◽  
Systems Science ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Key Drivers ◽  
Effect Estimation ◽  
Inference Methods

Abstract A society’s social structure and the interactions of its members determine when key drivers of health occur, for how long they last, and how they operate. Yet, it has been unclear whether causal inference methods can help us find meaningful interventions on these fundamental social drivers of health. Galea and Hernán propose we place hypothetical interventions on a spectrum and estimate their effects by emulating trials, either through individual-level data analysis or systems science modeling (Am J Epidemiol. 2020;189(3):167–170). In this commentary, by way of example in health disparities research, we probe this “closer engagement of social epidemiology with formal causal inference approaches.” The formidable, but not insurmountable, tensions call for causal reasoning and effect estimation in social epidemiology that should always be enveloped by a thorough understanding of how systems and the social exposome shape risk factor and health distributions. We argue that one way toward progress is a true partnership of social epidemiology and causal inference with bilateral feedback aimed at integrating social epidemiologic theory, causal identification and modeling methods, systems thinking, and improved study design and data. To produce consequential work, we must make social epidemiology more causal and causal inference more social.

scholarly journals Do People in Conservative States Really Watch More Porn? A Hierarchical Analysis

2020 ◽  
Vol 6 ◽  
pp. 237802312090847
Author(s):  
Samuel L. Perry ◽  
Andrew L. Whitehead
Keyword(s):  
State Level ◽  
Ecological Fallacy ◽  
Hierarchical Analysis ◽  
Regression Analyses ◽  
Individual Level ◽  
Pornography Consumption ◽  
Level Data ◽  
Political Conservatism ◽  
Nationally Representative ◽  
Evangelical Identity

Recent studies have found that state-level religious and political conservatism is positively associated with various aggregate indicators of interest in pornography. Such studies have been limited, however, in that they either did not include data measuring actual consumption patterns and/or did not include data on individuals (risking the ecological fallacy). This study overcomes both limitations by incorporating state-level data with individual-level data and a measure of pornography consumption from a large nationally representative survey. Hierarchical linear regression analyses show that, in the main, state-level religious and political characteristics do not predict individual-level pornography consumption, and individual-level religiosity and political conservatism predict less recent pornography consumption. However, interactions between individual-level evangelical identity and state-level political conservatism indicate that evangelicals who live in more politically conservative states report the highest rates of pornography consumption. These findings thus provide more nuanced support for previous research linking religious and political conservatism with greater pornography consumption.

Ecological Regression Versus Homogeneous Units: A Specification Analysis

1978 ◽  
Vol 2 (2) ◽  
pp. 172-193 ◽  
Author(s):  
Allan J. Lichtman ◽  
Laura Irwin Langbein
Keyword(s):  
Native American ◽  
Empirical Work ◽  
State Level ◽  
Ecological Fallacy ◽  
Individual Level ◽  
Past Behavior ◽  
Statistical Measures ◽  
Ecological Regression ◽  
Level Data ◽  
The Individual

Writing more than twenty five years ago, W. S. Robinson assailed the assumption implicit in much empirical work that statistical measures computed for aggregate units—states, provinces, counties, cities, wards, school districts—could be used in place of corresponding measures for the individuals comprising these units. Robinson was not the first scholar to expose the pitfalls of naive inferences from group level data to individual level behavior. But he first brought this problem forcefully to the attention of practicing social scientists. Focusing on the Pearson product moment correlation coefficient (r), Robinson proved that an aggregate level coefficient need not be equal in value to the corresponding individual level coefficient. Blending empirical examples with mathematical demonstration, Robinson showed that when the individual level correlation between being a native American and being able to read was computed for state level percentages of natives and literates, its value changed from .118 to -.526. Thus an investigator relying on correlations computed for the American states would not even correctly assess the direction of the relationship between nativity and literacy. Coining new jargon, Robinson used the term “ecological fallacy” to describe a naive inference from the group to the individual level of analysis.The reverberations of Robinson’s work are still being felt by those interested in the past behavior of individuals. Historians without access to survey research and experimental techniques must rely on data that have already been collected. Because such data so often pertain to aggregate units, historians frequently must use cross-level inference to estimate the behavior of individuals. Having paid virtually no attention to the methodology of cross-level inference for almost twenty years after the publication of Robinson’s work, historians have suddenly discovered the “ecological fallacy.” Authors dread to see the term “ecological fallacy” scribbled in the margins of their work; to fall victim to this fallacy is to forfeit one’s claim to methodological legitimacy.

Medicare and Medicaid Services Online

2013 ◽  
pp. 359-373 ◽  
Author(s):  
Mary Schmeida ◽  
Ramona McNeal
Keyword(s):  
Health Insurance ◽  
Multivariate Regression Analysis ◽  
The United States ◽  
Vulnerable Groups ◽  
Government Programs ◽  
Life Project ◽  
Demographic Groups ◽  
Individual Level ◽  
Level Data ◽  
Access To Health

Government initiatives in the United States have been passed in an effort to increase citizen usage of e-government programs. One such service is the availability of online health insurance information. However, not all demographic groups have been equally able to access these services, primarily the poor and rural American. As more legislation is passed, including the advancement of broadband services to remote areas, infrastructure barriers are being removed, opening access to Medicare and Medicaid websites for these vulnerable groups. The purpose of this chapter is to analyze factors predicting the impact of recent government actions on citizen access to health insurance information online. This topic is explored using multivariate regression analysis and individual level data from the Internet and American Life Project. The findings suggest that healthcare needs and quality of Internet access may be playing a more important role in health insurance information services than other factors.

Christian Right Horticulture: Grassroots Support in a Republican Primary Campaign

2008 ◽  
Vol 1 (1) ◽  
pp. 55-84 ◽  
Author(s):  
Paul A. Djupe ◽  
Jacob R. Neiheisel
Keyword(s):  
Social Structure ◽  
Christian Right ◽  
Vote Choice ◽  
Comprehensive Model ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Grassroots Support ◽  
Original Survey ◽  
Effective Group

AbstractSeizing upon the opportunity afforded by a Republican primary contest in which a candidate backed by the Christian Right took on a candidate with connections to the party establishment, we examine the strength of the Christian right at the grassroots in Ohio. Using individual-level data compiled from an original survey instrument administered to over 1,000 Republican primary voters just after the May, 2006 primary, we present a more comprehensive model of both Christian Right support and the effect of Christian Right support on the vote choice. Instead of assuming a grassroots presence underpinning the movement, we assert and test the argument that natural elements of the social structure inhibit effective group access to collections of supporters. In doing so, we provide an explanation for the often observed gulf between movement identifiers and opinion-based supporters.

Using Census Data to Investigate the Causes of the Ecological Fallacy

1998 ◽  
Vol 30 (5) ◽  
pp. 817-831 ◽  
Author(s):  
M Tranmer ◽  
D G Steel
Keyword(s):  
Census Data ◽  
Ecological Fallacy ◽  
Individual Level ◽  
Data Analyses ◽  
Level Statistics ◽  
Australian Census ◽  
Level Information ◽  
Small Area Statistics ◽  
The Individual ◽  
Level Analysis

The authors show how data from the 2% Sample of Anonymised Records (SAR) can be combined with data from the Small Area Statistics (SAS) database to investigate the causes of the ecological fallacy in an Enumeration District (ED) level analysis. A range of census variables are examined in three ‘SAR districts’ (local authority districts with populations of 120 000 or more, or combinations of contiguous districts with smaller populations) in England. Results of comparable analyses from the 1986 Australian census are also given. The ecological fallacy arises when results from an analysis based on area-level aggregate statistics are incorrectly assumed to apply at the individual level. In general the results are different because individuals in the same area tend to have similar characteristics: a phenomenon known as within-area homogeneity. A statistical model is presented which allows for within-area homogeneity. This model may be used to explain the effects of aggregation on variances, covariances, and correlations. A methodology is introduced which allows aggregate-level statistics to be adjusted by using individual-level information on those variables that explain much of the within-area homogeneity. This methodology appears to be effective in adjusting census data analyses, and the results suggest that the SAR is a valuable source of adjustment information for aggregate data analyses from census and other sources.

Sign in / Sign up

Export Citation Format

Share Document