scholarly journals Bayesian Reanalyses from Summary Statistics: A Guide for Academic Consumers

2017 ◽  
Author(s):  
Alexander Ly ◽  
Akash Raj ◽  
Alexander Etz ◽  
Maarten Marsman ◽  
Quentin Frederik Gronau ◽  
...  
Keyword(s):  
Social Sciences ◽  
Cognitive Dissonance ◽  
Open Source Software ◽  
Summary Statistics ◽  
Bayesian Paradigm ◽  
Continuous Scale ◽  
The Social ◽  
Single Number ◽  
Parameter Ranges ◽  
Statistical Preference

Across the social sciences, researchers have overwhelmingly used the classical statistical paradigm to draw conclusions from data, often focusing heavily on a single number: p. Recent years, however, have witnessed a surge of interest in an alternative statistical paradigm: Bayesian inference, in which probabilities are attached to parameters and models. We feel it is informative to provide statistical conclusions that go beyond a single number, and --regardless of one's statistical preference-- it can be prudent to report the results from both the classical and the Bayesian paradigm. In order to promote a more inclusive and insightful approach to statistical inference we show how the open-source software program JASP (jasp-stats.org) provides a set of comprehensive Bayesian reanalyses from just a few commonly-reported summary statistics such as t and N. These Bayesian reanalyses allow researchers --and also editors, reviewers, readers, and reporters-- to quantify evidence on a continuous scale, assess the robustness of that evidence to changes in the prior distribution, and gauge which posterior parameter ranges are more credible than others. The procedure is illustrated using the seminal Festinger and Carlsmith (1959) study on cognitive dissonance.

scholarly journals Bayesian Reanalyses From Summary Statistics: A Guide for Academic Consumers

2018 ◽  
Vol 1 (3) ◽  
pp. 367-374 ◽  
Author(s):  
Alexander Ly ◽  
Akash Raj ◽  
Alexander Etz ◽  
Maarten Marsman ◽  
Quentin F. Gronau ◽  
...  
Keyword(s):  
Social Sciences ◽  
Cognitive Dissonance ◽  
Open Source Software ◽  
Prior Distribution ◽  
Summary Statistics ◽  
Continuous Scale ◽  
The Social ◽  
Single Number ◽  
Parameter Ranges ◽  
Statistical Preference

Across the social sciences, researchers have overwhelmingly used the classical statistical paradigm to draw conclusions from data, often focusing heavily on a single number: p. Recent years, however, have witnessed a surge of interest in an alternative statistical paradigm: Bayesian inference, in which probabilities are attached to parameters and models. We feel it is informative to provide statistical conclusions that go beyond a single number, and—regardless of one’s statistical preference—it can be prudent to report the results from both the classical and the Bayesian paradigms. In order to promote a more inclusive and insightful approach to statistical inference, we show how the Summary Stats module in the open-source software program JASP ( https://jasp-stats.org ) can provide comprehensive Bayesian reanalyses from just a few commonly reported summary statistics, such as t and N. These Bayesian reanalyses allow researchers—and also editors, reviewers, readers, and reporters—to (a) quantify evidence on a continuous scale using Bayes factors, (b) assess the robustness of that evidence to changes in the prior distribution, and (c) gauge which posterior parameter ranges are more credible than others by examining the posterior distribution of the effect size. The procedure is illustrated using Festinger and Carlsmith’s (1959) seminal study on cognitive dissonance.

Teaching statistics in the context of social foresight. An applied approach based on the use of an open-source software

2015 ◽  
Vol 23 (2) ◽  
pp. 140-148
Author(s):  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Giuseppe Espa
Keyword(s):  
Social Sciences ◽  
Open Source ◽  
Open Source Software ◽  
Quantitative Methods ◽  
Descriptive Analysis ◽  
Real Data ◽  
Introductory Statistics ◽  
Content Type ◽  
The Social ◽  
Teaching Statistics

Purpose – The purpose of this paper is to present the contents and the didactic approach that characterize, respectively, the “Introductory Statistics with R” and “Statistics and Foresight” courses of the Master in Social Foresight. Design/methodology/approach – The two courses “Introductory Statistics with R” and “Statistics and Foresight” are designed to provide an introduction to quantitative methods in the social sciences with specific applications to social foresight. In particular, the first course introduces students to data analysis providing the necessary tools to study and represent socio-economic phenomena through graphical summaries and numerical measures. During the course, example applications based on the use of the open-source software R are shown. At the end, the students should be able to perform data management, conduct descriptive analysis of categorical and quantitative variables and analyze bivariate distributions. The subsequent course “Statistics and Foresight” presents the most efficient methods to make decisions in a context of uncertainty while visualizing the potential errors of wrong decisions and computing the probability of their occurrence. Findings – This paper is a description of an interesting and promising way of teaching applied statistics in social sciences. Practical implications – With the main aim of learning the correct use of statistics, specific attention is devoted to the use and interpretation of the aforementioned methods rather than to their theoretical aspects. Even in the second course, an important role is played by the treatment of real data by the use of the R software. Originality/value – This paper attempts to systematize a method of teaching statistics based on the practical use of open-source software.

scholarly journals The Challenge of Rival Versions of Moral Enquiry Within Leadership-As-Practice

2021 ◽  
pp. 1-7
Author(s):  
Kirk Mensch
Keyword(s):  
Social Sciences ◽  
Cognitive Dissonance ◽  
Moral Disengagement ◽  
Leadership Theory ◽  
Moral Foundations ◽  
Moral Philosophies ◽  
Moral Agents ◽  
The Social ◽  
Self Harm ◽  
Moral Enquiry

Herein, I clarify my concern regarding Raelin’s Leadership-as-Practice (L-A-P) and argue that inconsistent moral philosophies undermine the veracity of leadership theory, especially more recent democratic, shared, collective, and practice oriented theories; that this problem seems to be proliferating in the social sciences, and that this is especially concerning in socio-psychologically oriented theories. I contend that the moral foundations of L-A-P remain philosophically disquieting, unless it is understood as excluding moral agents other than those of a genealogical tradition, and that such exclusionary consequences in practice may lead to moral disengagement, which might then lead to cognitive dissonance and even self-harm.

scholarly journals The Concept of Sustainability on Social Media: A Social Listening Approach

2020 ◽  
Vol 12 (5) ◽  
pp. 2122 ◽  
Author(s):  
María Teresa Ballestar ◽  
Miguel Cuerdo-Mir ◽  
María Teresa Freire-Rubio
Keyword(s):  
Social Sciences ◽  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Language Processing ◽  
Open Source Software ◽  
Sustainable Management ◽  
Social Phenomena ◽  
The Social ◽  
Social Listening

The concept of sustainability has gone far beyond the issues of the sustainable management of natural and environmental resources. Nowadays, sustainability is part of the social sciences in a different way. The aim of this research was dual. Firstly, we analyzed the different contexts and areas of knowledge where this concept is used in society by using social listening on Twitter, one of the most popular social networks today. The sentiments of these conversations were rated to assess whether the feelings and perceptions of these conversations on the social network were positive or negative regarding the use of the concept. Also, we tested if these perceptions about the topic were attuned to other more formal fields, such as scientific research, or strategies followed nationally or internationally by agencies and organizations related to sustainability. The method used on this first part of the research consisted of an analysis of 15,000 tweets collected from Twitter using natural language processing (NLP) for clustering the main areas of knowledge of topics where the concept of sustainability was used, and the sentiment of these conversations on the social network. Secondly, we mapped the social network of users who generated or spread content regarding sustainability on Twitter within the period of observation. Social network analysis (SNA) focuses on the taxonomy of the network and its dynamics and identifies the most relevant players in terms of generation of conversation and also their referrers who spread their messages worldwide. For this purpose, we used Gephi, an open source software used for network analysis and visualization, that allows for the exploration and visualization of large networks of any kind, in depth. The findings of this research are new, not only because of the mix of technology and methods used for extracting data from Twitter and analyzing them from different perspectives, but also because they show that social listening is a powerful method for analyzing relevant social phenomena. Listening on social networks can be used more effectively than other more traditional processes to gather data that are more costly and time consuming and lack the momentum and spontaneity of digital conversations.

What Can We Learn From Factorial Surveys About Human Behavior?

Methodology ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Knut Petzold ◽  
Tobias Wolbring
Keyword(s):  
Social Sciences ◽  
Behavioral Intentions ◽  
Actual Behavior ◽  
Full Time ◽  
Factorial Survey ◽  
Survey Experiment ◽  
Intended Behavior ◽  
The Social ◽  
Survey Experiments ◽  
High Level

Abstract. Factorial survey experiments are increasingly used in the social sciences to investigate behavioral intentions. The measurement of self-reported behavioral intentions with factorial survey experiments frequently assumes that the determinants of intended behavior affect actual behavior in a similar way. We critically investigate this fundamental assumption using the misdirected email technique. Student participants of a survey were randomly assigned to a field experiment or a survey experiment. The email informs the recipient about the reception of a scholarship with varying stakes (full-time vs. book) and recipient’s names (German vs. Arabic). In the survey experiment, respondents saw an image of the same email. This validation design ensured a high level of correspondence between units, settings, and treatments across both studies. Results reveal that while the frequencies of self-reported intentions and actual behavior deviate, treatments show similar relative effects. Hence, although further research on this topic is needed, this study suggests that determinants of behavior might be inferred from behavioral intentions measured with survey experiments.

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