Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science

ABSTRACT

Scientific research of all kinds should be guided by statistical thinking: in the design and conduct of the study, in the disciplined exploration and enlightened display of the data, and to avoid statistical pitfalls in the interpretation of the results. However, formal, probability-based statistical inference should play no role in most scientific research, which is inherently exploratory, requiring flexible methods of analysis that inherently risk overfitting. The nature of exploratory work is that data are used to help guide model choice, and under these circumstances, uncertainty cannot be precisely quantified, because of the inevitable model selection bias that results. To be valid, statistical inference should be restricted to situations where the study design and analysis plan are specified prior to data collection. Exploratory data analysis provides the flexibility needed for most other situations, including statistical methods that are regularized, robust, or nonparametric. Of course, no individual statistical analysis should be considered sufficient to establish scientific validity: research requires many sets of data along many lines of evidence, with a watchfulness for systematic error. Replicating and predicting findings in new data and new settings is a stronger way of validating claims than blessing results from an isolated study with statistical inferences.     

Accepting and Negotiating Service Users' Choices in Mental Health Transition Meetings

Across Western welfare regimes, policies emphasize that service users should have more choices regarding their services. This article examines how service choices are presented, responded to and decided in interactions between service users and professionals in mental health transition meetings. Choice is often associated with consumerist user involvement ideas, but in mental health choice also relates to the democratic user involvement approach and to shared decision making between professionals and service users. The results of the study show that professionals construct service users as consumers by offering service options in choice making sequences, expecting users to make appropriate choices. Service users mostly act like consumers by responding to these choice options. However, the study also demonstrates that the professionals do not always accept the user's first choice but respond to them as non‐preferred. Sometimes, they also suggest choices on behalf of the users. In these ‘non‐accepting’ sequences, choices are negotiated in interaction between the parties, rather than users acting as autonomous choice makers. The sequences are based on two kinds of professional reasoning: first, the professional‐led needs assessment and, second, the structure of the service package that the user is being offered. This negotiation has elements of shared decision making and the ‘logic of care’. But it also has elements of paternalist control which challenge both consumerist and democratic service user involvement and suggests consideration of more collectively oriented service user actions.     

Understanding Gaps Between the Risk Perceptions of Wildland–Urban Interface (WUI) Residents and Wildfire Professionals

Research across a variety of risk domains finds that the risk perceptions of professionals and the public differ. Such risk perception gaps occur if professionals and the public understand individual risk factors differently or if they aggregate risk factors into overall risk differently. The nature of such divergences, whether based on objective inaccuracies or on differing perspectives, is important to understand. However, evidence of risk perception gaps typically pertains to general, overall risk levels; evidence of and details about mismatches between the specific level of risk faced by individuals and their perceptions of that risk is less available. We examine these issues with a paired data set of professional and resident assessments of parcel‐level wildfire risk for private property in a wildland–urban interface community located in western Colorado, United States. We find evidence of a gap between the parcel‐level risk assessments of a wildfire professional and numerous measures of residents’ risk assessments. Overall risk ratings diverge for the majority of properties, as do judgments about many specific property attributes and about the relative contribution of these attributes to a property's overall level of risk. However, overall risk gaps are not well explained by many factors commonly found to relate to risk perceptions. Understanding the nature of these risk perception gaps can facilitate improved communication by wildfire professionals about how risks can be mitigated on private lands. These results also speak to the general nature of individual‐level risk perception.     

Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria

Population and Environment - After a disaster, there is an urgent need for information on population mobility. Our analysis examines the suitability of Twitter data for measuring post-disaster...     

Disability, Eugenics and the Current Ideology of Segregation: a modern moral tale

Recently, an amalgamation of articles have appeared in a wide range of publications linking together community and school inclusion, and facilitated communication research as an unholy trinity of anti-empiricism eroding the disability fields. The authors of these critiques suggest that there exists a scientific basis for state institutions, segregated learning and a non-critical acceptance of traditional interpretations of expressive ability on the part of people with disabilities. In this article we expose not science, but an ideology of segregated control behind these claims. This ideology permeates the disabilityrelated professions and is cloaked in the language of the natural sciences. We trace this use of the natural sciences to the eugenics movement of the early twentieth century and explore the legacy of the ideology of control as it impacts current understanding of disability.     

Multiple roots of estimating functions

Estimating functions can have multiple roots. In such cases, the statistician must choose among the roots to estimate the parameter. Standard asymptotic theory shows that in a wide variety of cases, there exists a unique consistent root, and that this root will lie asymptotically close to other consistent (possibly inefficient) estimators for the parameter. For this reason, attention has largely focused on the problem of selecting this root and determining its approximate asymptotic distribution. In this paper, however, we concentrate on the exact distribution of the roots as a random set. In particular, we propose the use of higher-order root intensity functions as a tool for examining the properties of the roots and determining their most problematic features. The use of root intensity functions of first and second order is illustrated by application to the score function for the Cauchy location model.     

Implicit prejudicial biases in student learning: the effects of sexual orientation

In an investigation of students' potential biases toward gay and lesbian instructors, 93 female and 59 male undergraduates viewed a lecture, rated the instructor and perceived learning, and completed a lecture-retention test. Lectures were given by a man or woman, identified as straight or gay or lesbian. Sexual orientation did not affect the instructor evaluation or perceived learning ratings for any of the groups. Although sexual orientation did not affect the lecture-retention scores for the female students, learning by the male students was significantly lower with the gay male instructor than with the straight male instructor (p = .03), suggesting an implicit bias.