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Author(s):  
Susanne Schmitz ◽  
Michel Vaillant ◽  
Christell Renoux ◽  
Robert L. Konsbruck ◽  
Pierre Hertz ◽  
...  

2022 ◽  
Author(s):  
Christoph Beuthner ◽  
Florian Keusch ◽  
Henning Silber ◽  
Bernd Weiß ◽  
Jette Schröder

As our modern world has become increasingly digitalized, various types of data from different data domains are available that can enrich survey data. To link survey data to other sources, consent from the survey respondents is required. This article compares consent to data linkage requests for seven data domains: administrative data, smartphone usage data, bank data, biomarkers, Facebook data, health insurance data, and sensor data. We experimentally explore three factors of interest to survey designers seeking to maximize consent rates: consent question order, consent question wording, and incentives. The results of the study using a German online sample (n = 3,374) show that survey respondents have a relatively high probability of consent to share smartphone usage data, Facebook data, and biomarkers, while they are least likely to share their bank data in a survey. Of the three experimental factors, only the consent question order affected consent rates significantly. Additionally, the study investigated the interactions between the three experimental manipulations and the seven data domains, of which only the interaction between the data domains and the consent question order showed a consistent significant effect.


Econometrics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Myoung-Jin Keay

This paper presents a method for estimating the average treatment effects (ATE) of an exponential endogenous switching model where the coefficients of covariates in the structural equation are random and correlated with the binary treatment variable. The estimating equations are derived under some mild identifying assumptions. We find that the ATE is identified, although each coefficient in the structural model may not be. Tests assessing the endogeneity of treatment and for model selection are provided. Monte Carlo simulations show that, in large samples, the proposed estimator has a smaller bias and a larger variance than the methods that do not take the random coefficients into account. This is applied to health insurance data of Oregon.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Danika Bannasch ◽  
Thomas Famula ◽  
Jonas Donner ◽  
Heidi Anderson ◽  
Leena Honkanen ◽  
...  

Abstract Background Dog breeds are known for their distinctive body shape, size, coat color, head type and behaviors, features that are relatively similar across members of a breed. Unfortunately, dog breeds are also characterized by distinct predispositions to disease. We explored the relationships between inbreeding, morphology and health using genotype based inbreeding estimates, body weight and insurance data for morbidity. Results The average inbreeding based on genotype across 227 breeds was Fadj = 0.249 (95% CI 0.235–0.263). There were significant differences in morbidity between breeds with low and high inbreeding (H = 16.49, P = 0.0004). There was also a significant difference in morbidity between brachycephalic breeds and non-brachycephalic breeds (P = 0.0048) and between functionally distinct groups of breeds (H = 14.95 P < 0.0001). Morbidity was modeled using robust regression analysis and both body weight (P < 0.0001) and inbreeding (P = 0.013) were significant (r2 = 0.77). Smaller less inbred breeds were healthier than larger more inbred breeds. Conclusions In this study, body size and inbreeding along with deleterious morphologies contributed to increases in necessary health care in dogs.


2021 ◽  
Vol 4 (2) ◽  
pp. 126
Author(s):  
Mira Zakiah Rahmah ◽  
Aceng Komarudin Mutaqin

<p><strong>Abstract. </strong>This paper discusses the method of limited-fluctuation credibility, also known as classic credibility. Credibility theory is a technique for predicting future premium rates based on past experience data. Limited fluctuation credibility consists of two credibility, namely full credibility if Z = 1 and partial credibility if Z &lt;1. Full credibility is achieved if the amount of recent data is sufficient for prediction, whereas if the latest data is insufficient then the partial credibility approach is used. Calculations for full and partial credibility standards are used for loss measures such as frequency of claims, size of claims, aggregate losses and net premiums. The data used in this paper is secondary data recorded by the company PT. XYZ in 2014. This data contains data on the frequency of claims and the size of the policyholder's partial loss claims for motor vehicle insurance products category 4 areas 1. Based on the results of the application, the prediction of pure premiums for 2015 cannot be fully based on insurance data for 2014 because the credibility factor value is less than 1. So based on the limited-fluctuation credibility method, the prediction of pure premiums for 2015 must be based on manual values for pure premiums as well as insurance data for 2014. If manual values for pure premium is 2,000,000 rupiah, then the prediction of pure premium for 2015 is 1,849,342 rupiah.</p><p><strong>Keywords</strong><strong>: </strong>limited fluctuation credibility, full credibility, partial credibility and partial loss</p>


2021 ◽  
Vol 9 (33) ◽  
pp. 10198-10207
Author(s):  
Hong Ki Min ◽  
Se Hee Kim ◽  
Jong Han Choi ◽  
Kyomin Choi ◽  
Hae-Rim Kim ◽  
...  

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