The Experts below are selected from a list of 42 Experts worldwide ranked by ideXlab platform
Rense Corten - One of the best experts on this subject based on the ideXlab platform.
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measuring segregation in social networks
Social Networks, 2014Co-Authors: Michal Bojanowski, Rense CortenAbstract:Abstract Network homophily is a pattern in which ties are more likely to exist between nodes similar to each other. It is frequently observed for various types of social relations. At the same time, segregation is often encountered in urban areas as a tendency of families to occupy neighborhoods inhabited by other families similar to them. In this paper we conceptualize both phenomena as in the language of networks of interlinked positions occupied by a population of actors characterized by some node-level attribute. We review existing indexes and approaches to measuring the extent of homophily/segregation in social networks. We pursue an approach of, first, specifying a set of properties that a generic segregation Measure might possess, and which, in our view, are relevant in substantial contexts. Second, we check which Measures satisfy which properties. The use of Measures is illustrated with four empirical examples. Given the particular application and the need for some Descriptive Measure of segregation, the results presented in this paper can help in selecting an optimal Measure for the task at hand. We conclude that the most crucial aspects for the choice of a particular segregation Measure include (1) whether the network ties or actors’ attributes are assumed to be subject to change, and (2) how one should treat the presence of network isolates.
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measuring segregation in social networks
2011Co-Authors: Michal Bojanowski, Rense CortenAbstract:Network homophily is a pattern in which ties are more likely to exist between nodes similar to each other. It is frequently observed for various types of social relations. At the same time, segregation is often encountered in urban areas as a tendency of families to occupy neighborhoods inhabited by other families similar to them. In this paper we conceptualize both phenomena as in the language of networks of interlinked positions occupied by a population of actors characterized by some node-level attribute. We review existing indexes and approaches to measuring the extent of homophily/segregation in social networks. We pursue an axiomatic-like approach by first specifying a set of basic properties that a generic segregation Measure might possess, and which, in our view, are relevant in substantial contexts. We check which Measures satisfy which properties. Given the particular application and the need for some Descriptive Measure of segregation, the results presented in this paper can help in selecting an optimal Measure for the task at hand. We conclude that the most crucial aspects for the choice of a particular segregation Measure include (1) whether the network ties or actors' attributes are assumed to be subject to change, and (2) how one should treat the presence of network isolates.
Joseph L Gastwirth - One of the best experts on this subject based on the ideXlab platform.
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median based Measures of inequality reassessing the increase in income inequality in the u s and sweden
Statistical journal of the IAOS, 2014Co-Authors: Joseph L GastwirthAbstract:The increase in income inequality, due to a shift in favor of the upper end in the United States and other countries, has become a public policy concern. This paper shows that the Gini index, G, underestimates the rate of increase in inequality because a shift of income towards the top incomes increases both the numerator and denominator of G. A modified index (G2) ,w hich replaces the mean in the denominator by the median, indicates that income inequality in the United States grew at about twice the rate as the Gini index from 1967 to 2012. The analysis accounts for the effect of the changes made in the survey collection process in 1994. In contrast with the United States, while income inequality increased in Sweden, the shift in favor of the upper income region was less pronounced. The index G2 is readily computed from the mean, median and Gini index, published by many national statistical agencies. Although G2 may not be appropriate for some analytic purposes, it is an easily calculated summary Descriptive Measure that is more sensitive to important changes in the income distribution than the Gini index. Most other indices placing greater weight on the upper end of the income distribution must be calculated from micro-data.
Fabian J Theis - One of the best experts on this subject based on the ideXlab platform.
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the ad coefficient as a Descriptive Measure of the within group agreement of ratings
British Journal of Mathematical and Statistical Psychology, 2010Co-Authors: Ludwig Kreuzpointner, Patricia Simon, Fabian J TheisAbstract:The a(d) coefficient was developed to Measure the within-group agreement of ratings. The underlying theory as well as the construction of the coefficient are explained. The a(d) coefficient ranges from 0 to 1, regardless of the number of scale points, raters, or items. With some limitations the Measure of the within-group agreement of different groups and groups from different studies is directly comparable. For statistical significance testing, the binomial distribution is introduced as a model of the ratings' random distribution given the true score of a group construct. This method enables a decision about essential agreement and not only about a significant difference from 0 or a chosen critical value. The a(d) coefficient identifies a single true score within a group. It is not provided for multiple true score settings. The comparison of the a(d) coefficient with other agreement indices shows that the new coefficient is in line with their outcomes, but does not result in infinite or inappropriate values.
Michal Bojanowski - One of the best experts on this subject based on the ideXlab platform.
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measuring segregation in social networks
Social Networks, 2014Co-Authors: Michal Bojanowski, Rense CortenAbstract:Abstract Network homophily is a pattern in which ties are more likely to exist between nodes similar to each other. It is frequently observed for various types of social relations. At the same time, segregation is often encountered in urban areas as a tendency of families to occupy neighborhoods inhabited by other families similar to them. In this paper we conceptualize both phenomena as in the language of networks of interlinked positions occupied by a population of actors characterized by some node-level attribute. We review existing indexes and approaches to measuring the extent of homophily/segregation in social networks. We pursue an approach of, first, specifying a set of properties that a generic segregation Measure might possess, and which, in our view, are relevant in substantial contexts. Second, we check which Measures satisfy which properties. The use of Measures is illustrated with four empirical examples. Given the particular application and the need for some Descriptive Measure of segregation, the results presented in this paper can help in selecting an optimal Measure for the task at hand. We conclude that the most crucial aspects for the choice of a particular segregation Measure include (1) whether the network ties or actors’ attributes are assumed to be subject to change, and (2) how one should treat the presence of network isolates.
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measuring segregation in social networks
2011Co-Authors: Michal Bojanowski, Rense CortenAbstract:Network homophily is a pattern in which ties are more likely to exist between nodes similar to each other. It is frequently observed for various types of social relations. At the same time, segregation is often encountered in urban areas as a tendency of families to occupy neighborhoods inhabited by other families similar to them. In this paper we conceptualize both phenomena as in the language of networks of interlinked positions occupied by a population of actors characterized by some node-level attribute. We review existing indexes and approaches to measuring the extent of homophily/segregation in social networks. We pursue an axiomatic-like approach by first specifying a set of basic properties that a generic segregation Measure might possess, and which, in our view, are relevant in substantial contexts. We check which Measures satisfy which properties. Given the particular application and the need for some Descriptive Measure of segregation, the results presented in this paper can help in selecting an optimal Measure for the task at hand. We conclude that the most crucial aspects for the choice of a particular segregation Measure include (1) whether the network ties or actors' attributes are assumed to be subject to change, and (2) how one should treat the presence of network isolates.
Raul Coimbra - One of the best experts on this subject based on the ideXlab platform.
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rib and sternum fractures in the elderly and extreme elderly following motor vehicle crashes
Accident Analysis & Prevention, 2011Co-Authors: Vishal Bansal, Carol Conroy, David W Chang, Gail T Tominaga, Raul CoimbraAbstract:As the population ages, the need to protect the elderly during motor vehicle crashes becomes increasingly critical. This study focuses on causation of elderly rib and sternum fractures in seriously injured elderly occupants involved in motor vehicle crashes. We used data from the Crash Injury Research and Engineering Network (CIREN) database (1997-2009). Study case criteria included occupant (≥ 65 years old) drivers (sitting in the left outboard position of the first row) or passengers (sitting in the first row right outboard position) who were in frontal or side impacts. To avoid selection bias, only occupants with a Maximum Abbreviated Injury Scale (MAIS) 3 (serious) or greater severity injury were included in this study. Odds ratios were used as a Descriptive Measure of the strength of association between variables and Chi square tests were used to determine if there was a statistically significant relationship between categorical variables. Of the 211 elderly (65-79 years old) occupants with thoracic injury, 92.0% had rib fractures and 19.6% had sternum fractures. For the 76 extreme elderly (80 years or older) with thoracic injury, 90.4% had rib fractures and 27.7% had sternum fractures. Except for greater mortality and more rib fractures caused by safety belts, there were no differences between the extreme elderly and the elderly occupants. Current safety systems may need to be redesigned to prevent rib and sternum fractures in occupants 80 years and older.