The Average Response Method of Scaling

1990 ◽  
Vol 15 (1) ◽  
pp. 9-38 ◽  
Author(s):  
Albert E. Beaton ◽  
Eugene G. Johnson
Keyword(s):  
Linear Models ◽  
Predictive Distribution ◽  
Average Response ◽  
Individual Level ◽  
Multiple Imputations ◽  
Plausible Values ◽  
Scale Scores ◽  
Using Data ◽  
The Individual ◽  
Response Method

The average response method (ARM) of scaling nonbinary data was developed to scale the data from the assessments of writing conducted by the National Assessment of Educational Progress (NAEP). The ARM applies linear models and multiple imputations technologies to characterize the predictive distribution of the person-level average of ratings over a pool of exercises when each person has responded to only a few of the exercises. The derivations of “plausible values” from the individual-level distributions of potential scale scores are given. Conditions are provided for the unbiasedness of estimates based on the plausible values, and the potential magnitude of the bias when the conditions are not met is indicated. Also discussed is how the plausible values allow for an accounting of the uncertainties due to the sampling of individuals and to the incomplete information on each sampled individual. The technique is illustrated using data from the assessment of writing.

scholarly journals Pro-Environmental Behavior in an Aging World: Evidence from 31 Countries

2021 ◽  
Vol 18 (4) ◽  
pp. 1748
Author(s):  
Yan Wang ◽  
Feng Hao ◽  
Yunxia Liu
Keyword(s):  
Linear Models ◽  
Population Change ◽  
Population Aging ◽  
Environmental Behavior ◽  
National Level ◽  
The Elderly ◽  
Human Beings ◽  
Individual Level ◽  
Contemporary World ◽  
The Individual

Population change and environmental degradation have become two of the most pressing issues for sustainable development in the contemporary world, while the effect of population aging on pro-environmental behavior remains controversial. In this paper, we examine the effects of individual and population aging on pro-environmental behavior through multilevel analyses of cross-national data from 31 countries. Hierarchical linear models with random intercepts are employed to analyze the data. The findings reveal a positive relationship between aging and pro-environmental behavior. At the individual level, older people are more likely to participate in environmental behavior (b = 0.052, p < 0.001), and at the national level, living in a country with a greater share of older persons encourages individuals to behave sustainably (b = 0.023, p < 0.01). We also found that the elderly are more environmentally active in an aging society. The findings imply that the longevity of human beings may offer opportunities for the improvement of the natural environment.

scholarly journals On “Nationology”: The Gravitational Field of National Culture

2021 ◽  
pp. 002202212110447
Author(s):  
Plamen Akaliyski ◽  
Christian Welzel ◽  
Michael Harris Bond ◽  
Michael Minkov
Keyword(s):  
Gravitational Field ◽  
Cultural Values ◽  
National Culture ◽  
Random Noise ◽  
Religious Groups ◽  
Individual Values ◽  
Individual Level ◽  
Collective Phenomenon ◽  
Using Data ◽  
The Individual

Nations have been questioned as meaningful units for analyzing culture due to their allegedly limited variance-capturing power and large internal heterogeneity. Against this skepticism, we argue that culture is by definition a collective phenomenon and focusing on individual differences contradicts the very concept of culture. Through the “miracle of aggregation,” we can eliminate random noise and arbitrary variation at the individual level in order to distill the central cultural tendencies of nations. Accordingly, we depict national culture as a gravitational field that socializes individuals into the orbit of a nation’s central cultural tendency. Even though individuals are also exposed to other gravitational forces, subcultures in turn gravitate within the limited orbit of their national culture. Using data from the World Values Survey, we show that individual values cluster in concentric circles around their nation’s cultural gravity center. We reveal the miracle of aggregation by demonstrating that nations capture the bulk of the variation in the individuals’ cultural values once they are aggregated into lower-level territorial units such as towns and sub-national regions. We visualize the gravitational force of national cultures by plotting various intra-national groups from five large countries that form distinct national clusters. Contrary to many scholars’ intuitions, alternative social aggregates, such as ethnic, linguistic, and religious groups, as well as diverse socio-demographic categories, add negligible explained variance to that already captured by nations.

Disentangling Differences in Homicide Incarceration Rates by Immigration Status: A Comparison in Texas

2020 ◽  
pp. 001112872094096
Author(s):  
Erin A. Orrick ◽  
Alexander H. Updegrove ◽  
Alex R. Piquero ◽  
Tomislav Kovandzic
Keyword(s):  
Undocumented Immigrants ◽  
Immigrant Status ◽  
Immigration Status ◽  
Incarceration Rate ◽  
Individual Level ◽  
Crime And Punishment ◽  
Using Data ◽  
The Individual ◽  
Almost All ◽  
Immigration And Crime

Research addressing the purported relationship between immigration and crime remains popular, but some gaps remain under-explored. One important gap involves disentangling differences in crime and punishment by immigrant status, as measured across different definitions of immigration status and in relation to U.S. natives, at the individual level. Using data from Texas, results show that native-born U.S. citizens are incarcerated for homicide at higher rates than almost all immigrant groups. While the incarceration rate for undocumented immigrants was 24% greater than the rate for all foreign-citizens, this rate was significantly less than that for U.S. citizens. Among the immigrant status classifications available in this study, all were associated with lower incarceration rates for homicide than that of U.S. citizens.

scholarly journals Unravelling ecological analysis

2006 ◽  
Vol 2006 ◽  
pp. 1-18 ◽  
Author(s):  
D. G. Steel ◽  
M. Tranmer ◽  
D. Holt
Keyword(s):  
Linear Regression Analysis ◽  
Aggregate Data ◽  
Auxiliary Variables ◽  
Ecological Analysis ◽  
Individual Level ◽  
Ecological Regression ◽  
Australian Census ◽  
Using Data ◽  
The Individual

Ecological analysis involves analysing aggregate data for groups of individuals to make inferences about relationships at the individual level. Often the results of such analyses give badly biased estimates. This paper will consider the sources of bias in linear regression analysis using aggregate data. The role of variation of the individual level relationships between groups and the consequent within-group correlations and how these are related to auxiliary variables that characterise the differences between groups is considered. A method of adjusting ecological regression for the effects of auxiliary variables is described and evaluated using data from the 1991 Australian Census.

Redistribution under the Social Security benefit formula at the individual and household levels, 1992 and 2004

2012 ◽  
Vol 12 (1) ◽  
pp. 1-27 ◽  
Author(s):  
ALAN L. GUSTMAN ◽  
THOMAS L. STEINMEIER ◽  
NAHID TABATABAI
Keyword(s):  
Social Security ◽  
Labor Force Participation ◽  
Social Security Benefit ◽  
Household Level ◽  
Individual Level ◽  
The Social ◽  
High Earning ◽  
Using Data ◽  
The Individual ◽  
Over Time

AbstractStudies using data from the early 1990s suggested that while the progressive Social Security benefit formula succeeded in redistributing benefits from individuals with high earnings to individuals with low earnings, it was much less successful in redistributing benefits from households with high earnings to households with low earnings. Wives often earned much less than their husbands. As a result, much of the redistribution at the individual level was effectively from high earning husbands to their own lower earning wives. In addition, spouse and survivor benefits accrue disproportionately to women from high income households. Both factors mitigate redistribution at the household level. It has been argued that with the increase in the labor force participation and earnings of women, Social Security now should do a better job of redistributing benefits at the household level. To be sure, when we compare outcomes for a cohort with a household member age 51 to 56 in 1992 with those from a cohort born twelve years later, redistribution at the household level has increased over time. Nevertheless, as of 2004 there still is substantially less redistribution of benefits from high to low earning households than from high to low earning individuals.

scholarly journals Can education be personalised using pupils’ genetic data?

2019 ◽  
Author(s):  
Tim T Morris ◽  
Neil M Davies ◽  
George Davey Smith
Keyword(s):  
Predictive Power ◽  
Predictive Accuracy ◽  
Educational Performance ◽  
Phenotypic Data ◽  
Individual Level ◽  
Polygenic Scores ◽  
Prior Achievement ◽  
Using Data ◽  
The Individual ◽  
Potential Tool

AbstractThe increasing predictive power of polygenic scores for education has led to their promotion by some as a potential tool for genetically informed policy. How well polygenic scores predict educational performance conditional on other phenotypic data is however not well understood. Using data from a UK cohort study, we investigated how well polygenic scores for education predicted pupils’ realised achievement over and above phenotypic data that are available to schools. Across our sample, prediction of educational outcomes from polygenic scores were inferior to those from parental socioeconomic factors. There was high overlap between the polygenic score and achievement distributions, leading to weak predictive accuracy at the individual level. Furthermore, conditional on prior achievement polygenic scores were not predictive of later achievement. Our results suggest that while polygenic scores can be informative for identifying group level differences, they currently have limited use for predicting individual educational performance or for personalised education.

COMPOUND POISSON CLAIMS RESERVING MODELS: EXTENSIONS AND INFERENCE

2018 ◽  
Vol 48 (3) ◽  
pp. 1137-1156 ◽  
Author(s):  
Shengwang Meng ◽  
Guangyuan Gao
Keyword(s):  
Linear Models ◽  
Mean Squared Error ◽  
Predictive Distribution ◽  
Compound Poisson ◽  
Poisson Models ◽  
Squared Error ◽  
Run Off ◽  
Mean And Variance ◽  
The Individual ◽  
Over Dispersion

AbstractWe consider compound Poisson claims reserving models applied to the paid claims and to the number of payments run-off triangles. We extend the standard Poisson-gamma assumption to account for over-dispersion in the payment counts and to account for various mean and variance structures in the individual payments. Two generalized linear models are applied consecutively to predict the unpaid claims. A bootstrap is used to estimate the mean squared error of prediction and to simulate the predictive distribution of the unpaid claims. We show that the extended compound Poisson models make reasonable predictions of the unpaid claims.

scholarly journals A Synchrony-Based Classification Approach for Predicting Attitudes Using fNIRS

2020 ◽  
Author(s):  
Macrina C Dieffenbach ◽  
Grace S R Gillespie ◽  
Shannon M Burns ◽  
Ian A McCulloh ◽  
Daniel L Ames ◽  
...  
Keyword(s):  
Near Infrared ◽  
Neural Synchrony ◽  
Reference Groups ◽  
Functional Near Infrared Spectroscopy ◽  
Individual Level ◽  
Naturally Occurring ◽  
Neuroscience Research ◽  
Using Data ◽  
The Individual ◽  
Dispositional Differences

Abstract Social neuroscience research has demonstrated that those who are like-minded are also “like-brained.” Studies have shown that people who share similar viewpoints have greater neural synchrony with one another, and less synchrony with people who “see things differently.” Although these effects have been demonstrated at the group level, little work has been done to predict the viewpoints of specific individuals using neural synchrony measures. Furthermore, the studies that have made predictions using synchrony-based classification at the individual level used expensive and immobile neuroimaging equipment (e.g. fMRI) in highly controlled laboratory settings, which may not generalize to real-world contexts. Thus, this study uses a simple synchrony-based classification method, which we refer to as the neural reference groups approach, to predict individuals’ dispositional attitudes from data collected in a mobile “pop-up neuroscience” lab. Using functional near infrared spectroscopy (fNIRS) data, we predicted individuals’ partisan stances on a sociopolitical issue by comparing their neural timecourses to data from two partisan neural reference groups. We found that partisan stance could be identified at above-chance levels using data from dorsomedial prefrontal cortex (dmPFC). These results indicate that the neural reference groups approach can be used to investigate naturally-occurring, dispositional differences anywhere in the world.

Change Leadership and Employees’ Commitment to Change

2018 ◽  
Vol 17 (2) ◽  
pp. 83-93 ◽  
Author(s):  
Bin Ling ◽  
Yue Guo ◽  
Dusheng Chen
Keyword(s):  
Collective Identity ◽  
Self Efficacy ◽  
Positive Relationship ◽  
Employee Commitment ◽  
Change Leadership ◽  
Mediating Effect ◽  
Commitment To Change ◽  
Individual Level ◽  
Using Data ◽  
The Individual

Abstract. This research develops a multilevel motivation model to examine the mediating effect of collective identity and change self-efficacy on the relationship between change leadership and employee commitment to change. Our model is empirically tested using data collected from 647 employees within 110 teams. The results show that in addition to the positive relationship between change leadership and employee commitment to change, collective identity at the group level and change self-efficacy at the individual level significantly mediate the positive relationship between change leadership and employee commitment to change. This paper rounds off with a discussion of limitations and contributions from theoretical and practical perspectives.

800 Languages and Counting

2018 ◽  
Author(s):  
Carolyn Logan
Keyword(s):  
Public Opinion ◽  
Preliminary Analysis ◽  
Linguistic Diversity ◽  
Political Attitudes ◽  
Language Evolution ◽  
Linguistically Diverse ◽  
Individual Level ◽  
Diverse Communities ◽  
Using Data ◽  
The Individual

Using data on more than 800 home languages identified during Afrobarometer Round 5 surveys in 35 countries, as well as information on multilingualism gathered in 20 countries in Round 4, this chapter explores linguistic diversity and multilingualism at the individual level, within communities, and across countries. Afrobarometer data offer a unique perspective on the distribution of languages and language capabilities from the viewpoint of the users of language rather than those who study it. The chapter also identifies some of the challenges encountered in collecting public opinion data in linguistically diverse environments. The findings reveal that even in many rural zones many Africans are living within ethnically and linguistically diverse communities, and preliminary analysis suggests this may have important implications for social and political attitudes. The data have untapped potential for understanding language evolution and for studying language both as a product and as a variable driving attitudes and outcomes.

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