The Methods explains why measurements and data analysis contribute to testing Measurable Hypotheses.
Why do papers have a Methods section?
The Methods section is commonly thought of as answering the question: "How was the problem studied?" (Bolt and Bruins, 2012). The purpose of the Methods section is considered as describing the procedures and materials used to perform experiments, perhaps using a chronological framework (Greene, 2013).
However, a purely descriptive Methods section omits an important aspect of the Methods: the reasons (or "rationale") for the selected procedures and materials (Greene, 2010). Choosing appropriate procedures and materials can represent a substantial investment of time and effort. In established fields, there may be many viable options for methods (e.g. different commercial suppliers, different techniques, etc.). In less-established fields, experiments may require custom-developed procedures and techniques that required design, development, and refinement. In either case, the reasons for choosing particular methods over alternatives is an important component of scientific methods. Therefore, the Methods must explain, not simply describe, the methods of a study.
A more appropriate overall question for the Methods section of a scientific paper is:
WHY are the chosen methods necessary and appropriate to test the Measurable Hypotheses?
Using clear frameworks can help simplify a Methods section.
At the broadest level, Methods sections are commonly structured using a list framework. Methods sections often have at least three subheadings that identify the major components of experimental research (the list of elements within each section below is not exhaustive). For studies involving human participants, the Methods may include the sections:
1) Study Participants.
How many participants enrolled, and why the number of participants was appropriate.
Specific recruitment methods if relevant.
Age (mean +/- standard deviation), sex distribution and other important characteristics of participant population (e.g. mass, anthropometry, etc.), and reasons why the population was appropriate.
Strategies for ensuring that groups are comparable to each other and/or representative of a larger population (balancing, randomization, etc.).
Evidence that ethical and appropriate procedures were used. Assurance that all procedures were approved by relevant and required governing bodies (e.g. IRB, IACUC) in accordance with all relevant laws and regulations.
2) Procedures and Protocols.
Overall design of study (cross-sectional, cohort, etc.).
Treatments used and the purpose of each treatment, explained in detail.
Procedures used for controls and why necessary and appropriate.
All specific testing procedures and their purpose.
Data collection: measurements employed and why chosen over other measurement methods, where appropriate.
Specific equipment used and for what purpose.
Calibrations employed and why necessary.
3) Data Analysis.
How and why collected data were conditioned (e.g. filtering) and reduced (e.g. calculating means, etc.).
Normalizations employed and why appropriate.
Mathematical calculations employed and why (detailed mathematical derivations can be placed in an Appendix).
Statistical tests employed and why they were the most appropriate tests..
Particularly for papers by students, a fourth section can help organize and clarify thinking and presentation:
4) Hypothesis tests
The specific criteria (calculations, statistics, and judgments) that will be used to support or reject each measurable hypothesis. Hypothesis tests can be simple, declarative statements. For example "If the ankle, knee, and hip range of motion for elderly participants are all significantly less than ankle, knee, and hip motion for young participants, it will support the measurable hypothesis that elderly individuals will have significantly lower range of hip, knee, and ankle flexion-extension movement during moderate speed walking than young individuals."
Using repeated frameworks can simplify the Methods.
Goal - Procedure - Rationale.
The "goal" is typically a measurement that is necessary to test one or more Measurable Hypotheses. For clarity, major goals that require several procedures and/or materials can be identified with a subheading delimiting a group of related procedures. For example:
We measured oxygen consumption with indirect calorimetry during rest and during moderate-speed walking. Indirect calorimetry allows for measurements of metabolic energy expenditure and also the relative utilization of fat and carbohydrate (Ferrannini, 1988). We used a ..."
The goal is to measure oxygen consumption. The procedure is indirect calorimetry (during rest and walking). The rationale for using indirect calorimetry is that the technique measures energy expenditure and the fuel used to power metabolism. The rationale is supported with a reference to a more detailed explanation of indirect calorimetry (Ferrannini, 1988).
The Procedure-Rationale part of the framework can be repeated for each method used to achieve a goal:
References to past research can provide justification for methods.
Some techniques (such as indirect calorimetry) become so widely-used that they do not require an extensive rationale. Common techniques can be justified simply by using a reference to a past study that explains the technique in more detail (e.g. Ferrannini, 1988).
References can help justify most or all choices explained in the Methods. For example, selecting procedures that have been demonstrated to be effective by past studies can help to make audiences confident that the procedures are reliable and valid. Alternatively, study populations or procedures may be selected to differ from past research (requiring references to previous studies). Therefore, references to past studies strengthen the argument of the Methods section, by helping to explain why each method is appropriate for testing the Measurable Hypotheses.
All procedures in the Methods section contribute to testing one or more Measurable Hypothesis.
The purpose of the procedures and materials in the Methods section is to make measurements sufficient to test the Measurable Hypotheses of the study. Therefore, all explanations in the Methods section must be clearly necessary to test one or more Measurable Hypotheses.
Because Methods are conventionally structured around a list of standard sections, the connections between methods and hypotheses are often indirect and contextual. For example, the Methods may explain a procedure that results in a measurement used to test a hypothesis.
The fourth section of the Methods (Hypothesis Tests), can help readers understand more directly how each method contributes to testing a Measurable Hypothesis. By clearly stating the Measurable Hypotheses and explaining the specific criteria for supporting or rejecting the hypotheses, the Hypothesis Tests section can provide a valuable summary of the Methods section. The Hypothesis Tests section also provides a clear framework for the Results section.
Methods or measurements that do not contribute to testing hypotheses result in unnecessary text and can be removed.
Methods must be explained in sufficient detail for competent scientists to repeat the experiment.
A reasonable target audience for a scientific paper is a scientist in a different field. Therefore, methods must be explained with enough detail that competent scientists can replicate the procedures. Competent scientists can reasonably be expected to know how to perform basic mathematical and statistical calculations. Competent scientists can reasonably be expected to be able to look up references and use procedures explained in other studies. However, any terminology, procedures, or materials that are not common knowledge, or not justified with a reference, must be explained in the Methods section.