Indrajeet Patil

• Doctor of Philosophy
• Software Engineer at Preisenergie

Sacrificial moral dilemmas elicit a strong conflict between the motive to not personally harm someone and the competing motive to achieving the greater good, which is often described as the "utilitarian" response. Some prior research suggests that reasoning abilities and deliberative cognitive style are associated with endorsement of utilitarian so...

Graphical displays can reveal problems in a statistical model that might not be apparent from purely numerical summaries. Such visualizations can also be helpful for the reader to evaluate the validity of a model if it is reported in a scholarly publication or report. But, given the onerous costs involved, researchers often avoid preparing informat...

The statsExpressions package has two key aims: to provide a consistent syntax to do statistical analysis with tidy data, and to provide statistical expressions (i.e., pre-formatted in-text statistical results) for plotting functions. Currently, it supports common types of statistical approaches and tests: parametric, nonparametric, robust, and Baye...

Beyond the challenge of keeping up to date with current best practices regarding the diagnosis and treatment of outliers, an additional difficulty arises concerning the mathematical implementation of the recommended methods. Here, we provide an overview of current recommendations and best practices and demonstrate how they can easily and convenient...

Beyond the challenge of keeping up-to-date with current best practices regarding the diagnosis and treatment of outliers, an additional difficulty arises concerning the mathematical implementation of the recommended methods. Here, we provide an overview of current recommendations and best practices and demonstrate how they can easily and convenient...

In both theoretical and applied research, it is often of interest to assess the strength of an observed association. Existing guidelines also frequently recommend going beyond null-hypothesis significance testing and reporting effect sizes and their confidence intervals. As such, measures of effect sizes are increasingly reported, valued, and under...

The recent growth of data science is partly fueled by the ever-growing amount of data and the joint important developments in statistical modeling, with new and powerful models and frameworks becoming accessible to users. Although there exist some generic functions to obtain model summaries and parameters, many package specific modeling functions d...

Correlations tests are arguably one of the most commonly used statistical procedures, and are used as a basis in many applications such as exploratory data analysis, structural modelling, data engineering etc. In this context, we present correlation, a toolbox for the R language and part of the easystats collection, focused on correlation analysis....

The {datawizard} package for the R programming language provides a lightweight toolbox to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. T...

The {datawizard} package for the R programming language (R Core Team, 2021) provides a lightweight toolbox to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties...

The see package is embedded in the easystats ecosystem, a collection of R packages that operate in synergy to provide a consistent and intuitive syntax when working with statistical models in the R programming language (R Core Team, 2021). Most easystats packages return comprehensive numeric summaries of model parameters and performance. The see pa...

The see package is embedded in the easystats ecosystem, a collection of R packages that operate in synergy to provide a consistent and intuitive syntax when working with statistical models in the R programming language (R Core Team, 2021). Most easystats packages return comprehensive numeric summaries of model parameters and performance. The see pa...

People experience a strong conflict while evaluating actors who unintentionally harmed someone—her innocent intention exonerating her, while the harmful outcome incriminating her. Different people solve this conflict differently, suggesting the presence of dispositional moderators of the way the conflict is processed. In the present research, we ex...

https://joss.theoj.org/papers/10.21105/joss.03167

Although third-party punishment helps sustain group cooperation, might victim compensation provide third parties with superior reputational benefits? Across 24 studies (N = 21,296), we provide a comprehensive examination of the consequences of the choice between punishment and compensation. What do people infer from, and how do they respond to, the...

A crucial part of statistical analysis is evaluating a model's quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many competing models. Upon investigation, fit indices should also be reported both visually and nume...

Research hypotheses are often concerned with the difference between two groups and statistical tests provide indicators (like p-values or Bayes factors) about the evidence for or against such differences. The R package, ggsignif provides a quick way to visualize such pairwise indicators as an annotation in a plot, for example showing if a differenc...

Emotion has long been understood to play an important role in motivating moral beliefs and behavior. Recent work has shown that level of emotional arousal exerts a strong influence on decision-making in sacrificial moral dilemmas, with heightened levels of arousal associated with increased aversion to committing moral transgressions to maximize uti...

The recent growth of data science is partly fueled by the ever-growing amount of data and the joint important developments in statistical modeling, with new and powerful models and frameworks becoming accessible to users. Although there exist some generic functions to obtain model summaries and parameters, many package-specific modeling functions d...

Correlations tests are arguably one of the most commonly used statistical procedures, and are used as a basis in many applications such as exploratory data analysis, structural modelling, data engineering etc. In this context, we present correlation, a toolbox for the R language (R Core Team, 2019) and part of the easystats collection, focused on c...

Mature moral judgments rely both on a perpetrator’s intent to cause harm, and also on the actual harm caused—even when unintended. Much prior research asks how intent information is represented neurally, but little asks how even unintended harms influence judgment. We interrogate the psychological and neural basis of this process, focusing especial...

Mature moral judgments rely on the consideration of a perpetrator’s mental state as well as harmfulness of the outcomes produced. Prior work has focused primarily on the functional correlates of how intent information is neurally represented for moral judgments, but few studies have investigated whether individual differences in neuroanatomy can al...

Recent research has demonstrated impairments in social cognition associated with multiple sclerosis (MS). The present work asks whether these impairments are associated with atypical moral judgment. Specifically, we assessed whether MS patients are able to integrate information about intentions and outcomes for moral judgment (i.e., appropriateness...

This study investigated hypothetical moral choices in adults with high-functioning autism and the role of empathy and alexithymia in such choices. We used a highly emotionally salient moral dilemma task to investigate autistics’ hypothetical moral evaluations about personally carrying out harmful utilitarian behaviours aimed at maximizing welfare....

Although past research has established that the utilitarian bias (increased willingness to agree to personally kill someone for the greater good) in psychopathy on moral dilemmas stems from weaker negative affect at the prospect of harming others due to reduced harm aversion, it remains to be seen if this is owing to reduced aversion to witnessing...

Previous research shows that when people judge moral acceptability of others' harmful behaviour, they not only take into account information about the consequences of the act but also an actor's belief while carrying out the act. A two-process model has been proposed to account for this pattern of moral judgements and posits: (1) a causal process t...

Recent research with moral dilemmas supports dual-process model of moral decision making. This model posits two different paths via which people can endorse utilitarian solution that requires personally harming someone in order to achieve the greater good (e.g., killing one to save five people): (i) weakened emotional aversion to the prospect of ha...

Although research in moral psychology in the last decade has relied heavily on hypothetical moral dilemmas and has been effective in understanding moral judgment, how these judgments translate into behaviors remains a largely unexplored issue due to the harmful nature of the acts involved. To study this link, we follow a new approach based on a des...