scholarly journals Predicting Ideological Prejudice: A Pre-Registered Replication of Brandt (2017)

2018 ◽  
Author(s):  
Mark John Brandt
Keyword(s):  
Time Series ◽  
Simple Model ◽  
Political Ideology ◽  
Meta Analysis ◽  
Null Model ◽  
National Election ◽  
Target Group ◽  
Archival Data ◽  
Target Groups ◽  
Better Than

Brandt (2017) demonstrated that a simple model using the perceived ideology of a target group can predict the size and direction of the association between political ideology and prejudice. A meta-analysis of four studies showed that this simple ideology only model performs better than a null model and models using the perceived conventionalism, status, and choice of being a member of the target groups. This report describes a preregistered replication which uses data from the American National Election Study’s 2016 Time Series (N = 2616), archival data that was only made available after the study was preregistered. The findings of Brandt (2017) were replicated and the meta-analysis reported in Brandt (2017) is updated with these new data.

The Validity of Specific Cognitive Abilities for the Prediction of Training Success in Germany

2014 ◽  
Vol 13 (3) ◽  
pp. 123-133 ◽  
Author(s):  
Wiebke Goertz ◽  
Ute R. Hülsheger ◽  
Günter W. Maier
Keyword(s):  
Cognitive Abilities ◽  
Personnel Selection ◽  
Meta Analysis ◽  
Mental Ability ◽  
Occupational Category ◽  
General Mental Ability ◽  
Training Success ◽  
Specific Cognitive Abilities ◽  
Better Than

General mental ability (GMA) has long been considered one of the best predictors of training success and considerably better than specific cognitive abilities (SCAs). Recently, however, researchers have provided evidence that SCAs may be of similar importance for training success, a finding supporting personnel selection based on job-related requirements. The present meta-analysis therefore seeks to assess validities of SCAs for training success in various occupations in a sample of German primary studies. Our meta-analysis (k = 72) revealed operational validities between ρ = .18 and ρ = .26 for different SCAs. Furthermore, results varied by occupational category, supporting a job-specific benefit of SCAs.

Political bullshit receptivity and its correlates: a cross-cultural validation of the concept

2020 ◽  
Author(s):  
Vukašin Gligorić ◽  
Allard Feddes ◽  
Bertjan Doosje
Keyword(s):  
The Netherlands ◽  
Political Ideology ◽  
Voting Behavior ◽  
Free Market ◽  
Meta Analysis ◽  
The United States ◽  
Persuasive Communication ◽  
Lower Probability ◽  
Left Wing ◽  
Total N

Frankfurt defined persuasive communication that has no regard for truth, knowledge, or evidence as bullshit. Although there has been a lot of psychological research on pseudo-profound bullshit, no study examined this type of communication in politics. In the present research, we operationalize political bullshit receptivity as endorsing vague political statements, slogans, and political bullshit programs. We investigated the relationship of these three measures with pseudo-profound bullshit, ideology (political ideology, support for neoliberalism), populism, and voting behavior. Three pre-registered studies in different cultural settings (the United States, Serbia, The Netherlands; total N = 534) yielded medium to high intercorrelations between political bullshit measures and pseudo-profound bullshit, and good construct validity (hypothesized one-factor solution). A Bayesian meta-analysis showed that all political bullshit measures positively correlated with support for the free market, while only some positively correlated with social (political statements and programs) and economic conservatism (programs), and populism (programs). In the U.S., higher receptivity to political bullshit was associated with a higher probability that one voted for Trump (vs Clinton) in the past and higher intentions to vote for Trump (vs Biden and Sanders). In the Netherlands, higher receptivity to political bullshit predicted the intention to vote for the conservative-liberal People's Party for Freedom and Democracy. Exploratory analyses on merged datasets showed that higher receptivity to political bullshit was associated with a higher probability to vote for right-wing candidates/parties and lower probability for the left-wing ones. Overall, political bullshit endorsement showed good validity, opening avenues for research in political communication, especially when this communication is broad and meaningless.

Meta-Analysis and Time Series Modeling Allow a Systematic Review of Primary HIV-1 Drug-Resistant Prevalence in Latin America and Caribbean

2015 ◽  
Vol 13 (2) ◽  
pp. 125-142 ◽  
Author(s):  
Antonio Coelho ◽  
Ronald Moura ◽  
Ronaldo Silva ◽  
Anselmo Kamada ◽  
Rafael Guimaraes ◽  
...  
Keyword(s):  
Systematic Review ◽  
Time Series ◽  
Latin America ◽  
Meta Analysis ◽  
Drug Resistant ◽  
Time Series Modeling ◽  
Latin America And Caribbean ◽  
Hiv 1

scholarly journals Efficacy and safety of neoadjuvant therapy for HER2-positive early breast cancer: a network meta-analysis

2021 ◽  
Vol 13 ◽  
pp. 175883592110069
Author(s):  
Jie Zhang ◽  
Yushuai Yu ◽  
Yuxiang Lin ◽  
Shaohong Kang ◽  
Xinyin Lv ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Combination Chemotherapy ◽  
Target Therapy ◽  
Meta Analysis ◽  
Her2 Positive ◽  
Single Target ◽  
Dual Target ◽  
Better Than ◽  
Positive Breast Cancer

Aims: Currently, there are many approaches available for neoadjuvant therapy for human epidermal growth factor receptor 2 (HER2)-positive breast cancer that improve therapeutic efficacy but are also controversial. We conducted a two-step Bayesian network meta-analysis (NMA) to compare odds ratios (ORs) for pathologic complete response (PCR) and safety endpoints. Methods: The Cochrane Central Register of Controlled Trials, PubMed, Embase, and online abstracts from the American Society of Clinical Oncology and San Antonio Breast Cancer Symposium were searched comprehensively and systematically. Phase II/III randomised clinical trials for targeted therapy in at least one arm were included. Results: A total of 9779 published manuscripts were identified, and 36 studies including 10,379 patients were finally included in our analysis. The NMA of PCR showed that dual-target therapy is better than single-target therapy and combination chemotherapy is better than monochemotherapy. However, anthracycline did not bring extra benefits, whether combined with dual-target therapy or single-target therapy. On the other hand, the addition of endocrine therapy in the HER2-positive, hormone receptor (HR)-positive subgroup might have additional beneficial effects but without significant statistical difference. By performing a conjoint analysis of the PCR rate and safety endpoints, we found that ‘trastuzumab plus pertuzumab’ and ‘T-DM1 containing regimens’ were well balanced in terms of efficacy and toxicity in all target regimens. Conclusion: In summary, trastuzumab plus pertuzumab-based dual-target therapy with combination chemotherapy regimens showed the highest efficacy of all optional regimens. They also achieved the best balance between efficacy and toxicity. As our study showed that anthracycline could be replaced by carboplatin, we strongly recommended TCbHP as the preferred choice for neoadjuvant treatment of HER2-positive breast cancer. We also look forward to the potential value of T-DM1 in improving outcomes, which needs further study in future trials.

scholarly journals Adversarial Unsupervised Representation Learning for Activity Time-Series

2019 ◽  
Vol 33 ◽  
pp. 834-841 ◽  
Author(s):  
Karan Aggarwal ◽  
Shafiq Joty ◽  
Luis Fernandez-Luque ◽  
Jaideep Srivastava
Keyword(s):  
Time Series ◽  
Chronic Conditions ◽  
Empirical Evaluation ◽  
Representation Learning ◽  
Time Segment ◽  
Linear Classifiers ◽  
Daily Routines ◽  
Learning Technique ◽  
Prevention And Cure ◽  
Better Than

Sufficient physical activity and restful sleep play a major role in the prevention and cure of many chronic conditions. Being able to proactively screen and monitor such chronic conditions would be a big step forward for overall health. The rapid increase in the popularity of wearable devices pro-vides a significant new source, making it possible to track the user’s lifestyle real-time. In this paper, we propose a novel unsupervised representation learning technique called activ-ity2vecthat learns and “summarizes” the discrete-valued ac-tivity time-series. It learns the representations with three com-ponents: (i) the co-occurrence and magnitude of the activ-ity levels in a time-segment, (ii) neighboring context of the time-segment, and (iii) promoting subject-invariance with ad-versarial training. We evaluate our method on four disorder prediction tasks using linear classifiers. Empirical evaluation demonstrates that our proposed method scales and performs better than many strong baselines. The adversarial regime helps improve the generalizability of our representations by promoting subject invariant features. We also show that using the representations at the level of a day works the best since human activity is structured in terms of daily routines.

scholarly journals Intergenerational Bubbles of Beliefs for Sustainability

2020 ◽  
Vol 12 (24) ◽  
pp. 10652
Author(s):  
Keiichiro Kobayashi ◽  
Asako Chiba
Keyword(s):  
Simple Model ◽  
Political Ideology ◽  
Belief System ◽  
Future Generations ◽  
Current Generation ◽  
Dynamic Economy ◽  
Religious Doctrine

We constructed a simple model of a dynamic economy in which the current generation chooses to excessively consume, thereby rendering society unsustainable. In such an economy, we assumed that a notional bubbly asset emerges, and its value grows if the current generation conserves adequate resources for future generations. Provided that the bubbly asset is considered valuable, the current generation chooses to conserve resources, rendering the economy sustainable. The condition for sustainability is that the value of this asset grows intergenerationally and indefinitely. The asset represents a belief system, such as a religious doctrine or a political ideology. Results imply that, to restore sustainability, a new intergenerational belief system must be identified, and its value grows indefinitely.

scholarly journals Quirky patterns in time-series of estimates of recruitment could be artefacts

2014 ◽  
Vol 72 (1) ◽  
pp. 111-116 ◽  
Author(s):  
M. Dickey-Collas ◽  
N. T. Hintzen ◽  
R. D. M. Nash ◽  
P-J. Schön ◽  
M. R. Payne
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Reference Points ◽  
Fish Stocks ◽  
Stock Recruitment ◽  
Modelling Assumptions ◽  
Meta Analyses ◽  
Recruitment Model ◽  
Recruitment Time

Abstract The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

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