Do cooperatives participation and technology adoption improve farmers’welfare in China?A joint analysis accounting for selection bias

This study examines the impact of farmers’cooperatives participation and technology adoption on their economic welfare in China.A double selectivity model(DSM)is applied to correct for sample selection bias stemming from both observed and unobserved factors,and a propensity score matching(PSM)method is applied to calculate the agricultural income difference with counter factual analysis using survey data from 396 farmers in 15 provinces in China.The findings indicate that farmers who join farmer cooperatives and adopt agricultural technology can increase agricultural income by 2.77 and 2.35%,respectively,compared with those non-participants and non-adopters.Interestingly,the effect on agricultural income is found to be more significant for the low-income farmers than the high-income ones,with income increasing 5.45 and 4.51%when participating in farmer cooperatives and adopting agricultural technology,respectively.Our findings highlight the positive role of farmer cooperatives and agricultural technology in promoting farmers’economic welfare.Based on the findings,government policy implications are also discussed.

Gastric cardia adenocarcinoma in Taiwan Residents men:Positive associations due to selection bias

The factors associated with an increase in gastric cardia adenocarcinoma are poorly understood.Environmental factors such as Helicobacter pylori(H.pylori) infection and diet have been hypothesized to play a role in the recently increased risk of this disease,but additional studies are needed.In conducting studies to establish the relationship between potential risk factors and gastric cardia adenocarcinoma,it is necessary to carefully consider the role of bias.In a recently published study,the reported associations between H.pylori as well as post-meal physical exertion and gastric cardia adenocarcinoma may have been greatly influenced by selection bias.

The Importance of Selection Bias in Internet Surveys

Nowadays, internet-based surveys are increasingly used for data collection, because their usage is simple and cheap. Also they give fast access to a large group of respondents. There are many factors affecting internet surveys, such as measurement, survey design and sampling selection bias. The sampling has an important place in selection bias in internet survey. In terms of sample selection, the type of access to internet surveys has several limitations. There are internet surveys based on restricted access and on voluntary participation, and these are characterized by their implementation according to the type of survey. It can be used probability and non-probability sampling, both of which may lead to biased estimates. There are different ways to correct for selection biases;poststratification or weighting class adjustments, raking or rim weighting, generalized regression modeling and propensity score adjustments. This paper aims to describe methodological problems about selection bias issues and to give a review in internet surveys. Also the objective of this study is to show the effect of various correction techniques for reducing selection bias.

Research on Retrospective Studies of Real-World Study and Its Selection Bias

Objective To provide references for improving the authenticity and reliability of the retrospective study results,thus improving the quality of evidence in the real world and strengthening drug supervision and decision-making.Methods Literature review was used to study the data sources,the characteristics of retrospective research,the sources and the corrections of selective bias in the real world.Results and Conclusion The biases in retrospective study mainly come from admission rate bias,patient rate bias,survivors bias,health user bias and symptom bias.

Security of biased BB84 quantum key distribution with finite resource

In the original BB84 quantum key distribution protocol, the states are prepared and measured randomly, which lose the unmatched detection results. To improve the sifting efficiency, biased bases selection BB84 protocol is proposed. Meanwhile, a practical quantum key distribution protocol can only transmit a finite number of signals, resulting in keys of finite length. The previous techniques for finite-key analysis focus mainly on the statistical fluctuations of the error rates and yields of the qubits. However, the prior choice probabilities of the two bases also have fluctuations by taking into account the finite-size effect. In this paper, we discuss the security of biased decoy state BB84 protocol with finite resources by considering all of the statistical fluctuations. The results can be directly used in the experimental realizations.

Assessing the Success of Masking in Acupuncture Trials:Further Insight

Editor： Hopton and MacPherson（1） are correct in noting that（1） attempts at masking are not always successful, hence（2） unsubstantiated claims of masking are not convincing, hence（3） guidance to cease assessing the success of masking should not be embraced. I take exception, however, to the authors calling this last point ＂controversial＂. I will concede that it is, in fact, controversial in the sense that tobacco was controversial at a time when certain medical groups still endorsed tobacco,