scholarly journals Investigating the Impact of Noneffortful Responses on Individual-Level Scores: Can the Effort-Moderated IRT Model Serve as a Solution?

2021 ◽  
pp. 014662162110138
Author(s):  
Joseph A. Rios ◽  
James Soland
Keyword(s):  
Classification Accuracy ◽  
Negative Impact ◽  
Parameter Recovery ◽  
Individual Level ◽  
Irt Model ◽  
Ability Estimates ◽  
Misclassification Rates ◽  
Individual Scores ◽  
3Pl Model ◽  
The Impact

Suboptimal effort is a major threat to valid score-based inferences. While the effects of such behavior have been frequently examined in the context of mean group comparisons, minimal research has considered its effects on individual score use (e.g., identifying students for remediation). Focusing on the latter context, this study addressed two related questions via simulation and applied analyses. First, we investigated how much including noneffortful responses in scoring using a three-parameter logistic (3PL) model affects person parameter recovery and classification accuracy for noneffortful responders. Second, we explored whether improvements in these individual-level inferences were observed when employing the Effort Moderated IRT (EM-IRT) model under conditions in which its assumptions were met and violated. Results demonstrated that including 10% noneffortful responses in scoring led to average bias in ability estimates and misclassification rates by as much as 0.15 SDs and 7%, respectively. These results were mitigated when employing the EM-IRT model, particularly when model assumptions were met. However, once model assumptions were violated, the EM-IRT model’s performance deteriorated, though still outperforming the 3PL model. Thus, findings from this study show that (a) including noneffortful responses when using individual scores can lead to potential unfounded inferences and potential score misuse, and (b) the negative impact that noneffortful responding has on person ability estimates and classification accuracy can be mitigated by employing the EM-IRT model, particularly when its assumptions are met.

scholarly journals Investigating the Impact of Noneffortful Responses on Individual-Level Scores: Can the Effort-Moderated IRT Model Serve as a Solution?

2021 ◽  
Author(s):  
Joseph Rios ◽  
Jim Soland
Keyword(s):  
Classification Accuracy ◽  
Negative Impact ◽  
Parameter Recovery ◽  
Individual Level ◽  
Irt Model ◽  
Ability Estimates ◽  
Misclassification Rates ◽  
Individual Scores ◽  
3Pl Model ◽  
The Impact

Suboptimal effort is a major threat to valid score-based inferences. While the effects of such behavior have been frequently examined in the context of mean group comparisons, minimal research has considered its effects on individual score use (e.g., identifying students for remediation). Focusing on the latter context, this study addressed two related questions via simulation and applied analyses. First, we investigated how much including noneffortful responses in scoring using a three-parameter logistic (3PL) model affects person parameter recovery and classification accuracy for noneffortful responders. Second, we explored whether improvements in these individual-level inferences were observed when employing the Effort Moderated IRT (EM-IRT) model under conditions in which its assumptions were met and violated. Results demonstrated that including 10% noneffortful responses in scoring led to average bias in ability estimates and misclassification rates by as much as 0.15 SDs and 7% respectively. These results were mitigated when employing the EM-IRT model, particularly when model assumptions were met. However, once model assumptions were violated, the EM-IRT model’s performance deteriorated, though still outperforming the 3PL model. Thus, findings from this study show that: (a) including noneffortful responses when using individual scores can lead to potential unfounded inferences and potential score misuse; and (b) the negative impact that noneffortful responding has on person ability estimates and classification accuracy can be mitigated by employing the EM-IRT model, particularly when its assumptions are met.

Trust, Ethnicity and Integrity in East Africa: Experimental Evidence from Kenya and Tanzania

2017 ◽  
Vol 2 (1) ◽  
pp. 88-123 ◽  
Author(s):  
Dominic Burbidge ◽  
Nic Cheeseman
Keyword(s):  
Ethnic Diversity ◽  
Negative Impact ◽  
Common Knowledge ◽  
Individual Level ◽  
Trust Games ◽  
Negative Effect ◽  
Experimental Games ◽  
The Individual ◽  
The Impact ◽  
First Time

AbstractPolitical economy comparisons of Kenya and Tanzania have often found the political salience of ethnicity to be far higher in the former than the latter, with a negative impact on intercommunal trust. This difference has tended to be explained on the basis of the different kinds of leadership that the two countries experienced after independence. However, these findings have typically been demonstrated using aggregate or survey data. This paper assesses the salience of ethnicity at the individual level for the first time, deploying monetized two-round trust games in urban Kenya and Tanzania. The experimental games isolate the comparative impact of common knowledge of ethnicity and integrity among a quasi-random selection of 486 citizens. Verifying previous findings, we observe higher levels of trust and trustworthiness in Tanzania as compared with Kenya. Further, in comparison with Kenya, any shared knowledge of ethnic identities in Tanzania leads players to transfer fewer resources, while common knowledge that both players are “honest” led to higher transfers there than in Kenya. These results provide robust evidence of higher levels of trust in Tanzania, and of the negative effect in that country of common knowledge of ethnicity on levels of cooperation. The findings demonstrate the way in which political context can shape the impact of ethnic diversity, and encourage further experimental research that looks at the intersubjective dynamics of social cooperation.

FOUR DECADES OF POVERTY AND CONSUMPTION IN CHINA

2020 ◽  
Vol 65 (supp01) ◽  
pp. 117-138
Author(s):  
JINXIAN WANG ◽  
CHEN WANG ◽  
YAN ZHANG
Keyword(s):  
Economic Growth ◽  
Income Distribution ◽  
Negative Impact ◽  
Poverty Index ◽  
Domestic Consumption ◽  
Individual Level ◽  
Provincial Level ◽  
The Individual ◽  
The Impact ◽  
Empirical Analyses

Since 2010, China’s miraculous growth has come to a halt and has shown steady deceleration. To re-accelerate economic growth, stimulating domestic consumption is a crucial way with fighting poverty as the key step. This paper attempts to explore the impact of poverty on resident consumption in China over the last four decades. Based on provincial data, we first simulate income distribution at the individual level and provide moderate poverty profiles at the provincial level. The empirical analyses are then conducted to gauge the poverty impacts using the estimated poverty index. Results show that (1) moderate poverty has decreased sharply in China, with the best achievement in Beijing, Shanghai and Guangdong; (2) moderate poverty exerts a significantly negative impact on resident consumption; and (3) when poverty increases, resident consumption on household equipment decreases the most, while resident consumption on food, transportation, and telecommunication decreases the least.

scholarly journals Environmental Stressors: The Mental Health Impacts of Living Near Industrial Activity

2005 ◽  
Vol 46 (3) ◽  
pp. 289-305 ◽  
Author(s):  
Liam Downey ◽  
Marieke Van Willigen
Keyword(s):  
Mental Health ◽  
Negative Impact ◽  
Well Being ◽  
Health Impacts ◽  
Toxic Release Inventory ◽  
Neighborhood Disorder ◽  
Industrial Activity ◽  
Individual Level ◽  
The Poor ◽  
The Impact

A growing literature examines whether the poor, the working class, and people of color are disproportionately likely to live in environmentally hazardous neighborhoods. This literature assumes that environmental characteristics such as industrial pollution and hazardous waste are detrimental to human health, an assumption that has not been well tested. Drawing upon the sociology of mental health and environmental inequality studies, we ask whether industrial activity has an impact on psychological well-being. We link individual-level survey data with data from the U.S. Census and the Toxic Release Inventory and find that residential proximity to industrial activity has a negative impact on mental health. This impact is both direct and mediated by individuals' perceptions of neighborhood disorder and personal powerlessness, and the impact is greater for minorities and the poor than it is for whites and wealthier individuals. These results suggest that public health officials need to take seriously the mental health impacts of living near industrial facilities.

scholarly journals DAMPAK REDENOMINASI TERHADAP INFLASI INDONESIA: PENANGANAN MISSING MENGGUNAKAN METODE CASE DELETION, PMM, RF DAN BAYESIAN

2019 ◽  
Vol 3 (3) ◽  
pp. 272-286
Author(s):  
Windri Wucika Bemi ◽  
Rani Nooraeni
Keyword(s):  
Economic Growth ◽  
Classification Accuracy ◽  
Historical Data ◽  
Negative Impact ◽  
Economic Factors ◽  
Macroeconomic Variables ◽  
Case Deletion ◽  
The Third ◽  
Bayesian Linear Regression ◽  
The Impact

Indonesia is the country with the third largest currency digit after Vietnam and Zimbabwe. In 2010, Indonesia conveyed a discourse on the application of rupiah redenomination, but in its implementation it was necessary to estimate the economic factors that would be affected, especially inflation, where inflation was one of the decisive indicators of the success of the redenomination policy of the currency. To estimate the impact of redenomination on inflation, Indonesia can reflect on the historical data of countries that have implemented the policy. Based on historical data, a model can be applied to Indonesia. Historical data includes macroeconomic variables and forms of government. To get a model with better precision, complete data needs to be considered. The historical missing will make the inferencing obtained invalid and important information that can be used for analysis also diminishes. The case deletion method, mean matching predictive, random forest, and bayesian linear regression can be used to handle it. The results showed that there were 38.18% missing data from total observations and the case deletion method as the best method. Then the condition of hyperinflation, economic growth, and the index of government forms significantly impacted inflation after the implementation of redenomination. So, if Indonesia applies redenomination between the period 2010-2017, with the classification accuracy of 64.71%, it is estimated that it will have a negative impact because the inflation will increase after redenomination is implemented.

scholarly journals A General Unfolding IRT Model for Multiple Response Styles

2018 ◽  
Vol 43 (3) ◽  
pp. 195-210 ◽  
Author(s):  
Chen-Wei Liu ◽  
Wen-Chung Wang
Keyword(s):  
Response Style ◽  
Response Styles ◽  
Parameter Estimates ◽  
Data Set ◽  
Parameter Recovery ◽  
New Model ◽  
Irt Model ◽  
Irt Models ◽  
Strongly Agree ◽  
The Impact

It is commonly known that respondents exhibit different response styles when responding to Likert-type items. For example, some respondents tend to select the extreme categories (e.g., strongly disagree and strongly agree), whereas some tend to select the middle categories (e.g., disagree, neutral, and agree). Furthermore, some respondents tend to disagree with every item (e.g., strongly disagree and disagree), whereas others tend to agree with every item (e.g., agree and strongly agree). In such cases, fitting standard unfolding item response theory (IRT) models that assume no response style will yield a poor fit and biased parameter estimates. Although there have been attempts to develop dominance IRT models to accommodate the various response styles, such models are usually restricted to a specific response style and cannot be used for unfolding data. In this study, a general unfolding IRT model is proposed that can be combined with a softmax function to accommodate various response styles via scoring functions. The parameters of the new model can be estimated using Bayesian Markov chain Monte Carlo algorithms. An empirical data set is used for demonstration purposes, followed by simulation studies to assess the parameter recovery of the new model, as well as the consequences of ignoring the impact of response styles on parameter estimators by fitting standard unfolding IRT models. The results suggest the new model to exhibit good parameter recovery and seriously biased estimates when the response styles are ignored.

Candidate Sexual Orientation Didn't Matter (in the Way You Might Think) in the 2015 UK General Election

2018 ◽  
Vol 112 (3) ◽  
pp. 713-720 ◽  
Author(s):  
GABRIELE MAGNI ◽  
ANDREW REYNOLDS
Keyword(s):  
Sexual Orientation ◽  
Negative Impact ◽  
Demographic Characteristics ◽  
Individual Level ◽  
Rapid Social Change ◽  
Political Experience ◽  
Original Dataset ◽  
Level Data ◽  
And Gender ◽  
The Impact

Does sexual orientation and gender identity matter at election time? While previous literature has explored the effect of candidate gender and ethnicity on electoral results, this is the first study to quantitatively investigate the impact of sexual orientation. We build an original dataset combining individual-level data on more than 3,000 candidates in the 2015 UK election with sociodemographic indicators at the constituency level. In addition to sexual orientation and other demographic characteristics, we include candidate education, political experience, and campaign spending. We find that LGBT candidates generally do not have a negative impact on party vote share. Even in more conservative environments, LGBT candidates perform at least as well as their straight counterparts. This work is important to understand the consequences of descriptive representation and, relatedly, how rapid social change happens.

scholarly journals How Much Is Too Much? The Influence of Work Hours on Social Development: An Empirical Analysis for OECD Countries

2019 ◽  
Vol 16 (24) ◽  
pp. 4914
Author(s):  
Bei Liu ◽  
Hong Chen ◽  
Xin Gan
Keyword(s):  
Developing Countries ◽  
Social Development ◽  
Organizational Performance ◽  
Negative Impact ◽  
Negative Relationship ◽  
Developed Countries ◽  
Oecd Countries ◽  
Work Hours ◽  
Individual Level ◽  
The Impact

Work is a cornerstone of social development. Quantifying the impact on development of fluctuations in work hours is important because longer work hours increasingly seem to be the norm. Based on an integrative perspective that combines individual, organizational, and social factors, we constructed a model using data from 31 member countries of the Organisation for Economic Co-operation and Development (OECD). The proposed model was used to test the effect of work hours on different levels and to propose feasible suggestions accordingly. The results show that people in developing countries work more hours per week than those in developed countries, and that males work longer hours than females. Furthermore, regression analysis shows that current work hours are having a negative impact on development in OECD countries, especially in developing countries where people are working longer hours. Longer hours, in other words, do not promote development effectively. Specifically, work hours at the individual level are negatively related to health. At the level of organization, work hours are a reverse indicator of organizational performance, and at the level of society, there is a negative relationship between work hours and economic development. This study provides support for the proposition by the International Labour Organization to reduce work hours, and it facilitates our understanding of the relationship between work hours and social development.

The role of individual cultural traits and proactivity in an organizational setting

2014 ◽  
Vol 37 (4) ◽  
pp. 348-366 ◽  
Author(s):  
Kerry D. Carson ◽  
David S. Baker ◽  
Patricia A. Lanier
Keyword(s):  
Negative Impact ◽  
Uncertainty Avoidance ◽  
Equation Modeling ◽  
Proactive Behavior ◽  
Content Type ◽  
Individual Level ◽  
Cultural Traits ◽  
Proactive Behaviors ◽  
The Individual ◽  
The Impact

Purpose – The purpose of this research is to assess the impact of espoused individual cultural traits on proactive behaviors within an organizational environment. While there have been many reports about the positive outcomes of proactivity, there is much less known about the antecedents, particularly those related to culture. Design/methodology/approach – Sales employees (n=147) in a multi-national organization from Australia, Canada, New Zealand, the UK, and the USA were surveyed to assess the impact of cultural trait influences on proactive behavior at the individual level. Using linear regression and partial least squares structural equation modeling, three independent variables were found to be significant antecedents to proactive behavior. Findings – Long-term orientation positively influenced proactive behaviors as did uncertainty avoidance. Uncertainty avoidance was hypothesized to have a negative impact on proactive behaviors, but the results of this study implied that individuals found it safer to adjust to a fluid environment rather than to remain inflexible. No relationship was found between power distance and proactivity. Masculinity was found to be positively related to proactive behaviors but collectivism was not. Research limitations/implications – The results of this study should be limited to its own population and not generalized to larger, more culturally diverse populations which were not represented in the sample. Practical implications – This study provides better understanding of managerial proactive behavior related to cultural traits, particularly in the domain of field sales. Originality/value – This study is unique in that it explores individual proactivity in an organizational selling environment related to cultural traits at the individual level.

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