Between these extremes lies the bulk of social science theory or models, what Merton called. Philosophers of science have long debated the meaning of the term empirical. As we state here, in one sense the empirical nature of science means that assertions about the world must be warranted by, or at least constrained by, explicit observation of it. However, we recognize that in addition to direct observation, strategies like logical reasoning and mathematical analysis can also provide empirical support for scientific assertions.
Subsequently, however, analysis of light energy absorbed by Earth, measured from the content of organic material in geological sediment cores, raised doubts about this correlation as a causal mechanism e. The modest change in eccentricity did not make nearly enough difference in incident sunlight to produce the required change in thermal absorption.
Examples of such mid-range theories or explanatory models can be found in the physical and the social sciences. These theories are representations or abstractions of some aspect of reality that one can only approximate by such models. Molecules, fields, or black holes are classic explanatory models in physics; the genetic code and the contractile filament model of muscle are two in biology.
He based the hypothesis on astronomical observations showing that the regions above and below the ecliptic are laden with cosmic dust, which would cool the planet. Farley had begun his research project in an effort to refute the Muller inclination model, but discovered—to his surprise— that cosmic dust levels did indeed wax and wane in sync with the ice ages.
As an immediate cause of the temperature change, Muller proposed that dust from space would influence the cloud cover on Earth and the amount of greenhouse gases—mainly carbon dioxide—in the atmosphere. Indeed, measurements of oxygen isotopes in trapped air bubbles and other properties from a ,year-long Antarctic ice core by paleoceanographer Nicholas Shackleton provided more confirming evidence. Still, no one knows how orbital variations would send the carbon dioxide into and out of the atmosphere.
And there are likely to be other significant geologic factors besides carbon dioxide that control climate. There is much work still to be done to sort out the complex variables that are probably responsible for the ice ages. Theory enters the research process in two important ways. First, scientific research may be guided by a conceptual framework, model, or theory.
Researchers seek to test whether a theory holds up under certain circumstances. Here the link between question and theory is straightforward. For example, Putnam based his work on a theoretical conception of institutional performance that related civic engagement and modernization.
A research question can also devolve from a practical problem Stokes, ; see discussion above. In this case, addressing a complex problem like the relationship between class size and student achievement may require several theories. Indeed, the findings from the Tennessee class size reduction study see Box have led to several efforts to devise theoretical understandings of how class size reduction may lead to better student achievement.
Scientists are developing models to understand differences in classroom behavior between large and small classes that may ultimately explain and predict changes in achievement Grissmer and Flannagan, That is, the choice of what to observe and how to observe it is driven by an organizing conception—explicit or tacit— of the problem or topic. Thus, theory drives the research question, the use of methods, and the interpretation of results.
Research methods—the design for collecting data and the measurement and analysis of variables in the design—should be selected in light of a research question, and should address it directly. Methods linked directly to problems permit the development of a logical chain of reasoning based. The process of posing significant questions or hypotheses may occur, as well, at the end of a study e. For clarity of discussion, we separate out the link between question and method see Principle 3 and the rigorous reasoning from evidence to theory see Principle 4.
In the actual practice of research, such a separation cannot be achieved. Debates about method—in many disciplines and fields—have raged for centuries as researchers have battled over the relative merit of the various techniques of their trade. The simple truth is that the method used to conduct scientific research must fit the question posed, and the investigator must competently implement the method.
Particular methods are better suited to address some questions rather than others. The rare choice in the mid s in Tennessee to conduct a randomized field trial, for example, enabled stronger inferences about the effects of class size reduction on student achievement see Box than would have been possible with other methods.
This link between question and method must be clearly explicated and justified; a researcher should indicate how a particular method will enable competent investigation of the question of interest. Moreover, a detailed description of method—measurements, data collection procedures, and data analyses—must be available to permit others to critique or replicate the study see Principle 5.
Finally, investigators should identify potential methodological limitations such as insensitivity to potentially important variables, missing data, and potential researcher bias.
The choice of method is not always straightforward because, across all disciplines and fields, a wide range of legitimate methods—both quantitative and qualitative—are available to the researcher. For example when considering questions about the natural universe—from atoms to cells to black holes—profoundly different methods and approaches characterize each sub-field.
While investigations in the natural sciences are often dependent on the use of highly sophisticated instrumentation e.
For example, in two Danish zoologists identified an entirely new phylum of animals from a species of tiny rotifer-like creatures found living on the mouthparts of lobsters, using only a hand lens and light microscope Wilson, , p. However, the Glass and Smith study was criticized e. Some subsequent reviews reached conclusions similar to Glass and Smith e. In the midst of controversy, the Tennessee state legislature asked just this question and funded a randomized experiment to find out, an experiment that Harvard statistician Frederick Mosteller , p.
If a research conjecture or hypothesis can withstand scrutiny by multiple methods its credibility is enhanced greatly. As Webb, Campbell, Schwartz, and Sechrest , pp. The experiment began with a cohort of students who entered kindergarten in , and lasted 4 years. After third grade, all students returned to regular size classes. Although students were supposed to stay in their original treatment conditions for four years, not all did. Three findings from this experiment stand out.
First, students in small classes outperformed students in regular size classes with or without aides. Second, the benefits of class-size reduction were much greater for minorities primarily African American and inner-city children than others see, e. And third, even though students returned to regular classes in fourth grade, the reduced class-size effect persisted in affecting whether they took college entrance examinations and on their examination performance Krueger and Whitmore, Interestingly, in balancing the size of the effects of class size reduction with the costs, the Tennessee legislature decided not to reduce class size in the state Ritter and Boruch, New theories about the periodicity of the ice ages, similarly, were informed by multiple methods e.
The integration and interaction of multiple disciplinary perspectives—with their varying methods—often accounts for scientific progress Wilson, ; this is evident, for example, in the advances in understanding early reading skills described in Chapter 2.
This line of work features methods that range from neuroimaging to qualitative classroom observation. We close our discussion of this principle by noting that in many sciences, measurement is a key aspect of research method. This is true for many research endeavors in the social sciences and education research, although not for all of them.
If the concepts or variables are poorly specified or inadequately measured, even the best methods will not be able to support strong scientific inferences. The history of the natural sciences is one of remarkable development of concepts and variables, as well as the tools instrumentation to measure them. Measurement reliability and validity is particularly challenging in the social sciences and education Messick, Sometimes theory is not strong enough to permit clear specification and justification of the concept or variable.
Sometimes the tool e. Sometimes the use of the measurement has an unintended social consequence e. And sometimes error is an inevitable part of the measurement process. In the physical sciences, many phenomena can be directly observed or have highly predictable properties; measurement error is often minimal.
However, see National Research Council [] for a discussion of when and how measurement in the physical sciences can be imprecise. In sciences that involve the study of humans, it is essential to identify those aspects of measurement error that attenuate the estimation of the relationships of interest e. By investigating those aspects of a social measurement that give rise to measurement error, the measurement process itself will often be improved. Regardless of field of study, scientific measurements should be accompanied by estimates of uncertainty whenever possible see Principle 4 below.
The extent to which the inferences that are made in the course of scientific work are warranted depends on rigorous reasoning that systematically and logically links empirical observations with the underlying theory and the degree to which both the theory and the observations are linked to the question or problem that lies at the root of the investigation.
This chain of reasoning must be coherent, explicit one that another researcher could replicate , and persuasive to a skeptical reader so that, for example, counterhypotheses are addressed. All rigorous research—quantitative and qualitative—embodies the same underlying logic of inference King, Keohane, and Verba, This inferential reasoning is supported by clear statements about how the research conclusions were reached: What assumptions were made?
How was evidence judged to be relevant? How were alternative explanations considered or discarded? How were the links between data and the conceptual or theoretical framework made? The nature of this chain of reasoning will vary depending on the design of the study, which in turn will vary depending on the question that is being investigated. Will the research develop, extend, modify, or test a hypothesis?
Does it aim to determine: What works? How does it work? Under what circumstances does it work? If the goal is to produce a description of a complex system, such as a subcellular organelle or a hierarchical social organization, successful inference may rather depend on issues of fidelity and internal consistency of the observational techniques applied to diverse components and the credibility of the evidence gathered.
The research design and the inferential reasoning it enables must demonstrate a thorough understanding of the subtleties of the questions to be asked and the procedures used to answer them. Putnam used multiple methods to subject to rigorous testing his hypotheses about what affects the success or failure of democratic institutions as they develop in diverse social environments to rigorous testing, and found the weight of the evidence favored.
This principle has several features worthy of elaboration. Nature Biotechnology , ;29 9 Bioinformatics ;28 9 We have a range of RRPs in various stages of development, scientific assessment and commercialization.
Because our RRPs do not burn tobacco, they produce far lower quantities of harmful and potentially harmful compounds than found in cigarette smoke. What is coming next? Further challenges and datathons are currently in planning. References 1. Suppose now that H implies a series of observations O 1 , O 2 , That is, some of the observational consequences of the theory are found to be true. Does E confirm H, and to what extent?
This is the fundamental question of inductive logic and scientific method. What constitutes a significant test and confirmation to the theory? Several logical points are important. No finite list of observations exhaustively confirms a theory with universal generalizations; and different types of additional evidence have very different incremental effects on the credibility of the theory.
What is an observation? This has been a main source of controversy in the philosophy of science, in that it has long been recognized that there is no sharp and permanent distinction between observation and theory.
Virtually all scientific observations are theory-laden. But the essential idea is that an empirical observation is a scientific belief with a relatively direct relationship between the evidence of the senses and the truth conditions of the statement, based on reliable techniques of data collection to which we can attach high rational credibility. Here, for example, we are to consider direct sensory observation, observation using instrumentation, interviews, records of price data, etc.
But they are relatively unburdened by currently controversial theories. Several general approaches to empirical evaluation of scientific hypotheses have been offered in the past century. First is the idea, most deeply explored by Carl Hempel, that we should draw out the deductive consequences of a theory; evaluate the truth of some of those consequences using observation and instrumentation; and assign a degree of warrant to the theory based on the volume of its confirmed observational consequences.
This approach constitutes the hypothetico-deductive theory of confirmation, and it represents the logical basis for the experimental method. The hypothesis should be distinctly put as a question, before making the observations which are to test its truth. In other words, we must try to see what the result of predictions from the hypothesis will be. The respect in regard to which the resemblances are noted must be taken at random.
We must not take a particular kind of predictions for which the hypothesis is known to be good. The failures as well as the successes of the predictions must be honestly noted. The whole proceeding must be fair and unbiased. Peirce, , p. The first rule anticipates preregistration e. Peirce distinguished three stages of scientific inquiry: deduction, induction, and abduction.
Adrianus Dingeman de Groot — was a Dutch methodologist whose ideas about scientific inquiry were inspired in part by Popper. This is the phase in which the creative researcher enjoys complete freedom:.
Only when this freedom is respected will room remain for the brilliant insight, for the imagination of the researcher. We added the Whewell-Peirce-Reichenbach distinction between the context of discovery and the context of justification. Once creative speculation has spawned a new hypothesis, this gives rise to new predictions, which can then be tested in a new experiment. The inductive evaluation of the outcome results in an updated knowledge base, after which the empirical cycle starts anew.
As did Peirce, de Groot repeatedly stressed the importance of maintaining the integrity of the empirical cycle and not allowing shortcuts, however beguiling e. Specifically, to test a new prediction, one needs a fresh data set: The old data that were used to generate the new prediction may not be reused to test that prediction:.
It is of the utmost importance at all times to maintain a clear distinction between exploration and hypothesis testing. The scientific significance of results will to a large extent depend on the question whether the hypotheses involved had indeed been antecedently formulated, and could therefore be tested against genuinely new materials.
It is a serious offense against the social ethics of science to pass off an exploration as a genuine testing procedure. Unfortunately, this can be done quite easily by making it appear as if the hypotheses had already been formulated before the investigation started. If an investigation into certain consequences of a theory or hypothesis is to be designed as a genuine testing procedure and not for exploration , a precise antecedent formulation must be available, which permits testable consequences to be deduced.
The tension between creativity and verification lies at the heart of most theories of scientific inquiry. As pointed out by later scientists, creativity and verification play complementary roles in different stages of the scientific process.
Early in the process, when hypotheses need to be generated from a present body of knowledge, the understanding may well be supplied with wings. But this is allowed only because in the next stages, it is hung with weights.
Without verification in place, the only recourse would be to adopt a mechanical, Baconian view of creativity. Moreover, creative processes benefit from having a reliable knowledge base, and this is something that the verification process helps establish.
As a method to ensure that creativity and verification retain their rightful place in the empirical cycle, preregistration presents a conceptually straightforward solution. However, preregistration is not a panacea. Of course, without the benefit of a preregistration protocol, it would be impossible to learn that primary outcome measures have been switched altogether.
A possible limitation of preregistration is that one might encounter unforeseen data patterns e. A method that could help here is blinding e. For instance, in the Dutilh et al. Only after the analyst had committed to a specific analysis was the blind lifted, and the proposed analyses applied—without any change—to the unshuffled data set. Note that the analyst did alter some of the preregistered analyses, but because the analyst was blinded, the end result nevertheless retained its confirmatory status.
A final concern is that preregistration as it is currently practiced is often not sufficiently specific Veldkamp, , chap. To protect against hindsight bias and confirmation bias, a proper preregistration document must indicate exactly what analyses are planned, leaving no room for doubt. But in the absence of an actual data set, this can sometimes be difficult to do in advance; consequently, the preregistration document may leave room for alternative interpretation e.
A possible way to alleviate this concern is to devise the analysis plan on the basis of one or more mock data sets e. In addition, a mock data set makes it easier to write specific analysis code that could later be executed mechanically on the real data set. As preregistration becomes more popular, new challenges may arise and new solutions will be developed to address these challenges. Although preregistration may have drawbacks, we do not believe that the increased focus on verification will hinder the discovery of new ideas.
Creativity and verification are not competing forces in a zero-sum game; instead, they are in a symbiotic relationship in which neither could function properly in the absence of the other. It turns out that our understanding needs both wings and weights. We thank the reviewers and Cornelis Menke for helpful comments on an earlier draft.
We are aware that all of the historical figures discussed in this article are both White and male. We hope and believe that this reflects the social prejudice of a bygone era rather than any personal prejudice on the part of the present authors. Among his varied academic exploits, Herschel named seven moons of Saturn and four moons of Uranus. In a time of increasing specialisation, Whewell appears as a vestige of an earlier era when natural philosophers dabbled in a bit of everything.
He researched ocean tides for which he won the Royal Medal , published work in the disciplines of mechanics, physics, geology, astronomy, and economics, while also finding the time to compose poetry, author a Bridgewater Treatise, translate the works of Goethe, and write sermons and theological tracts. The mode of suggestion by which, in abduction, the facts suggest the hypothesis is by resemblance ,—the resemblance of the facts to the consequences of the hypothesis.
Action Editor: Robert J. Sternberg served as action editor and editor-in-chief for this article. Declaration of Conflicting Interests: The author s declared that there were no conflicts of interest with respect to the authorship or the publication of this article.
Wagenmakers and NWO research talent Grant National Center for Biotechnology Information , U. Perspectives on Psychological Science. Perspect Psychol Sci. Published online Jul 2.
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