A Grad Student’s Dream:Creating the Perfect Manuscript

Howard Tyler

The Process• Address a problem, determine the question• Design the study to address the question• Perform the study• Appropriately analyze the data• Write the manuscript• Is this worth publishing? (Critique the project and manuscript)• Decide where to submit• Submit• Wait• Revise• Publish

Structure of a Manuscript

• Abstract

• Key Words or Phrases

• Introduction

• Materials and Methods

• Results

• Discussion

• Literature Cited

Order for Writing Manuscript• Materials and Methods (as you do the project)• Results (as you analyze the project)• Discussion (from your lit review, incorporating

your own data into it’s new place in the field)• Introduction• Literature Cited• Abstract• Key Words

Abstract

• Why this work was done

• How it was done

• What was found (with statistical evidence)

• What does it mean or why is it important

• Limited space (2500 keystrokes in JAS)

• No references

• Define abbreviations at first use, unless considered standard for that journal

Key Words or Phrases

• Limited by journal (six for JAS)

• Used as search criteria– Species– Variables tested– Response criteria

Introduction• Present your problem and it’s significance• How it relates to the larger field in this discipline• Address other relevant studies (not a complete literature

review)– Should include all information necessary to understand the rest

of the manuscript• Concepts explained and terms defined

– Critique studies that you include in introduction and discussion (don’t be a parrot for other authors, even the original authors)

• Conclude with study objective(s)• Limited space (2,000 keystrokes for JAS)

Materials and Methods

• For each biological, analytical or statistical procedure, a clear, repeatable description must be provided– A specific original reference can be provided

in place of description• Any modifications of referenced procedures must

be explained and justified

Materials and Methods, cont.• Provide a publication reference for the

methodology used in kits or validate yourself– Accuracy and sensitivity can vary between species and ages

• Provide a validation for assays – mean and CV for repeated analysis of a sample (both

between and within-assay if available) and the sensitivity (minimum amount or concentration detectable)

• Describe or consider both validity (extent to which an instrument measures what it purports to measure) and reliability (extent to which an instrument provides consistent measurements)

Materials and Methods, cont.

• Describe procedural details for assays so they are repeatable– Centrifugal force in ×g, not rpm, and include

duration and temperature– Include volume of blood collected, container

used, and amount of preservative or anticoagulant (e.g., heparin, EDTA, etc.)

Materials and Methods, cont.• Describe diets

• Include dates of experimental activities (if appropriate)

• Describe animals used – breed, sex, age, body weight, and weighing

conditions (i.e., with or without restriction of feed and water)

• Describe surgical techniques

• Describe response variables and measurements

Materials and Methods, cont.

• Include statistical procedures used– If procedure is common to animal science,

just needs referencing with minimal description

– Describe the statistical model, classes, blocks, the experimental unit, and any restrictions in estimating parameters

• Report actual P-values

Experimental Design

• Describe study design, including the control group and any confounding factors that may reduce the validity of your study

• Sample schedule and method for sampling should be clearly described so that its representativeness to the population, to which the results will be generalized, can be assessed

• Sample size and calculations of statistical power should be clearly stated throughout manuscript

Experimental Units

• Experimental unit is defined as the smallest unit to which an individual treatment is imposed (animal vs. pen)

• Measurements on the same experimental unit over time cannot be considered independent experimental units

Materials and Methods, cont.

• WHAT IT IS NOT:– No background information, other than what is

necessary to describe specific assays or procedures

– No results– No conclusions– No interpretations

Results

• Results should be described primarily through tables and figures– Text supplements the tables and figures

• Elaborate and explain data, do NOT repeat numbers in text that were already presented in table or figure

– Data presented through text alone must specify “data not shown”

Tables and Figures• Tables and figures should independently “stand

alone”– No need to read text to understand the data

– Any author-defined abbreviations must be defined in EACH table and figure

• Table or figure? - depends on amount of data and most effective form to convey the information– The format chosen is important

• Line graphs imply knowledge of change between points, so do not use line graphs to display discrete data

Common Weaknesses in Results

• Inappropriate or incomplete statistics

• Omission of data

• Inconsistent or inaccurate data

• Unclear tables or figures

Discussion• Stands alone – no reference to your specific data• Restate the problem being addressed and summarize

how data addressed the problem• Interpret meaning and discuss significance• Potential sources of error in the data should be

discussed, and anomalies analyzed• Connect conclusions into the “big picture” by suggesting

the impact and(or) applications of this research– Discuss how your data will affect the field, what future

experiments could be carried out based on this research, or what affect the conclusions could have on the industry

Common Weaknesses in Discussion

• Over-interpretation of the data is the most common mistake made by authors

• Avoid speculative, unsubstantiated, or unsupported comments

Literature Cited

• To be listed, papers must be published or in press

• Be certain to use appropriate format for journals (in text and in Literature Cited)

• Remember to update this section as you revise manuscript

Points to Consider

• Authorship

• Let your data tell the story

• Critique your own manuscript objectively

Authorship

• Only include people that have significantly contributed to the conception, design, performance or analysis of the project– Include everyone that you can justify including

(paid help included)– Exclude everyone that you cannot justify

• Be generous with credit but authorship is not charity

Let The Data Rule

• If the design is right, the performance of the project is right, and the analysis is correct, then the data are always right– Do not try to explain away data that does not

agree with your hypothesis• A question beats a hypothesis because it

eliminates bias

– Discover what the data means rather than trying to tell the data what it should be

Critique Objectively

• YOU should be the first reviewer for your manuscript, and the most critical reviewer

• Look for flaws in design, in performance, in analysis, in interpretation– Make sure your manuscript represents ALL

possible interpretations fairly, not just your favorite hypothesis

- Follow reviewer best practices as you critique

Reviewing a Manuscript• What is the objective of this project?  Is it clearly stated?•  Is the experimental design appropriate to answer the question posed by the

objective?– Are the methods clearly outlined and appropriate?  – Were the methods carried out correctly?

• Is the statistical analysis clearly described and appropriate for the design of this experiment?

– Is the type of analysis appropriate?– Are the appropriate error terms and covariables utilized?

• Are the results clearly presented and described?– Are the data reasonable?

• Does the discussion explain the data from this experiment in the context of current knowledge in the field?

•  Are the conclusions valid and appropriate and clearly stated?•  FINALLY, is this manuscript publishable?

– You can declare it to be ready for publication or publishable following revisions or unacceptable for publication

Types of Fraud(from “Writing Scientific Manuscripts” (JYI, 2005)

• Plagiarism: Copying data, ideas, or work by other authors, without giving them credit. Discussing another researcher’s idea is not plagiarism, unless the author tries to pass it off as his/her own idea. Again, it is difficult for referees to catch plagiarism, unless they know what they are looking for.

• Fabrication: Inventing or faking results. It is almost impossible for peer review to catch this kind of fraud. It is usually discovered when other researchers try to reproduce the author’s results. Fabrication of results is never done innocently, and it leaves a permanent mark on the scientists’ career – if it doesn’t destroy it completely.

• Falsification: “Tweaking” or manipulating results. It is difficult for reviewers to catch this kind of fraud, and it is usually tough for other researchers too.

• Conflict of interest: If an author stands to make a significant financial profit from the results of a study – and does not state that explicitly – this constitutes a type of fraud. For example, if an author who owns stock in a pharmaceuticals company publishes a study indicating that a new drug by that company is simply fantastic, he must indicate that he owns stock in the company

Scientific Terminology TranslatedEllery Knake, U. of Illinois agronomist

• It has long been known = I haven’t bothered to look up the original reference

• Of great theoretical and practical importance = it was interesting to us

• Three of the samples were chosen for detailed study = the results of the other samples don’t make any sense

• It is generally believed that = I think

• It might be argued that = I have such a good answer for this objection and I shall now raise it

• It is clear that much additional work will be required before a complete

understanding is obtained = I don’t understand it

• Correct within an order of magnitude = wrong

• For which a satisfactory explanation is lacking = it is satisfactory but it doesn’t agree with

my conclusions

• Thanks are due to Dr. A for assistance with the experiment and to Dr. B for

valuable discussion = Dr. A did the work and Dr. B explained to us what it meant