Statistical Project for the Journal of the American Dietetic Association
Revised 6/30/06
Team members:
Sujata Archer
Carol Boushey
Barbara Bruemmer
Jeff Harris
Linda VanHorn
Global Goals and Objectives:
Goals:
A. Assure the quality of statistical methods and documentation in the Journal research
articles
B. Support statistical competence and capability for members of ADA including authors,
readers and students.
Objective:
1. Provide member value as a statistical resource
C. Develop a framework to deliver content on statistical methods using workshops, print
and web-based information.
Objectives:
1. Prioritize statistical methods for inclusion in the content. (Process
objective)
2. Include methods that have application in a range of practice areas and
baseline skills.
3. Promote the use of evidence based medicine and evidence based practice.
4. Develop statistical case studies that include:
a. Research scenario
b. Components for presentation
c. Model statement of statistical results
d. Resources and references
D) Assess unmet needs and revise deliverables on an ongoing basis
Project
Mechanism
Title / Content
Proposed date
Manuscripts
Print
Content:
Article2

Submit:_____

Statistical procedures (common procedures; some common
mistakes, such as clarification between different
correlation coefficients, using independent tests with
dependent samples)
Lead: CB/ JH
Describing Statistical Results:
Non-parametric/ parametric
Manuscripts
Manuscripts
Print
Print
Content: (See outline attached)
Publishing Nutrition Research: A Review of Nonparametric
Methods, Part 3
Article 3
Objectives
 The reader will understand the rationale for using
nonparametric methods.
 The reader will know the difference between parametric
and nonparametric statistical methods.
 The reader will list the nonparametric alternative to
parametric methods.
 The reader will apply the correct nonparametric test to the
appropriate variable situation.
Lead: JH
Content: (See outline attached)
Article 4

Statistical procedures (common procedures; some common
mistakes, such as clarification between different
correlation coefficients, using independent tests with
dependent samples
Target Date
Epidemiology
Lead: BB

ORs; RRs; CIs; Statistical Significance; Chance;
Confounding; Interaction;
Target Date
Summer 2006
Manuscripts
Print
Content
Article 5

Target Date:

Use of appropriate measurement and diagnostic tools
(validity testing, sensitivity, specificity, validity, reliability,
relative validity). Measurement issues with surveys
include: validity, content validity, construct validity,
internal consistency, and test-retest reliability.
Summer 2006
Lead: SA
Making appropriate inferences based on the study design,
sampling and results (a-priori hypothesis testing, post-hoc
analyzes, extrapolation)
'Research
Successful
Approaches'
Text
Contribute Chapters as outlined (see attached)
June 2006
Guidelines for
Authors
Web Page
Purpose: Provide additional resources on research design and
methods. Include links to statistical resources for analysis.
Target date mid-winter
FNCE
Workshop
Resubmit for FNCE 2007
2007
Interactive
Learning
“Sex, Drugs, and Diet…in Table 1: Research Design and
Biostatistics”
Integrate with stats project goals, e.g. manuscripts and
presentations.
August 16, 2006
Lead: Jeff Harris, DrPH, MPH, RD, LDN; West Chester
University of PA
Participants will interpret nutrition research designs and apply appropriate statistical solutions to their own
research projects. Further discussion of the quality control measures needed to strengthen accuracy and validity
of outcomes will be emphasized. The intention is to empower the dietitian to be an active initiator and
contributor to the research process that results in manuscripts that merit publication in the Journal of the
American Dietetic Association.
Carol J. Boushey
PhD, MPH, RD; Purdue
 Discuss the variety of nutrition-related research designs.
 Clarify the types of conclusions that can be drawn from each type of design.
 List the common errors researchers make when designing research projects and reporting on the results.
George P. McCabe PhD; Purdue
 Discuss how biostatistical methods can be applied to different types of data derived from nutrition-related
research designs.
 Comment on mistakes researchers make in the application and interpretation of biostatistical methods.

Discuss how researchers can best collaborate with a biostatistician to assist with conducting and reporting
research.
Completed Projects:
Guidelines for
Authors
Print
Statistics Project 2005
Author Guidelines (Refer to meeting materials)
Completed
Manuscripts
Print
‘Nutrition Research: Publishing Secrets from the Statistical Pros’
Published
Carol J. Boushey, Jeff Harris, Barb Bruemmer, Sujata Archer, Linda Van
Horn
Content:

Study Design (types, descriptions)

Study hypothesis, purpose, or objective
Publishing Nutrition Research: A Review of Nonparametric Methods, Part 3- Jeff
Objectives
1. The reader will understand the rationale for using nonparametric methods.
2. The reader will know the difference between parametric and nonparametric statistical
methods.
3. The reader will list the nonparametric alternative to parametric methods.
4. The reader will apply the correct nonparametric test to the appropriate variable situation.
I.
Introduction.
A.
Third installment of a series of papers on data analysis and statistical methods.
B.
Will cover univariate and bivariate nonparametric statistical tests.
C.
Contrasts nonparametric and parametric methods.
D.
Instructs on how to pick appropriate nonparametric test in different univariate and
bivariate situations.
II.
Rationale for Nonparametric Methods.
A.
Reasons for use of nonparametric tests.
III.
Advantages and Disadvantages of Nonparametric Methods.
IV.
Nonparametric Alternatives to Parametric Tests.
V.
Measures of Central Tendency for Nonparametric Situations.
A.
The median.
VI.
Wilcoxon Rank-Sum Test/Mann-Whitney Test.
VII. Wilcoxon Signed-Rank Test.
VIII. Kruskal-Wallis One-Way ANOVA by Ranks/Median Test.
IX.
The One-Sample Sign Test.
X.
Spearman Rank-Order Correlation Coefficient.
XII. Kolmogorov-Smirnov test
XIII. Friedman’s Test.
XIV. McNemar (the cousin to the paired t-test).
XV. The Chi-Square Test.
XVI. Conclusions.
Note: Will attempt to use examples from JADA.
Outline: Manuscript 4 – Barb
Introduction:
Acknowledge our series of articles to orient the reader
Wide use of epidemiological study designs in the nutrition field
Purpose
 Review of epi methods for potential investigators and scientific writers
 Review for readers of evidence based research
A. Examples of study questions (possibly 2 – one diet, one disease) that use epi methods –
Purpose of this section is to orient the reader and provide two –three scenarios that will
be used throughout the manuscript
B. The role of observational studies in advancing knowledge
Quality of studies as ranked in the Cochrane Collaborative – ‘Levels of Evidence’
Definitions – related to glossary as we have been doing
Causal hypotheses – limitations in epi studies
C. Basic framework of an epi study – terms and examples
Exposure
Outcome
Confounders
Bias
Misclassification
D. Designs
Purpose
Statement of the hypothesis
Strengths and weaknesses
1. Cross sectional
2. Case-Control
3. Cohort
E. Statistical tests
Common tests - χ2, logistic regression, survival analysis, Kaplan Meier
Odds Ratio, RR; CI, interpretation that findings are not due to chance (significance)
Appropriate presentation of results
F. Interpretation, limitations, resources
Research: Successful Approaches, third edition TOC
Updated: 5/15/2006
Contributors, Foreword, Introduction
Part 1: An Introduction to Discovery Through Research in Nutrition
and Dietetics
Ch 1: Steering Through the Research Continuum
Elaine R. Monsen, PhD, RD and Linda Van Horn, PhD, RD
Ch 2: Building the Research Foundation: The Research Question and
Study Design
Carol Boushey, PhD, MPH, RD, Jeffrey Harris, Dr.PH, RD,
Bruemmer, PhD, RD, and Sujata Archer, PhD, RD
Barbara
Part 2: Establishing and Maintaining a Research Environment
Ch 3: Conducting and Presenting Research Ethically
Elaine R. Monsen, PhD, RD
Ch 4: How to Write Proposals and Obtain Funding
Dianne Neumark- Sztainer, PhD, MPH, RD
Ch 5: Multi-disciplinary research
Madeleine Sigman-Grant, PhD, RD
Part 3: Descriptive Research
Ch 6: Descriptive Epidemiologic Research
Sujata Archer, PhD, RD
Ch 7: The Philosophy, Role, and Methods of Qualitative Inquiry
in Research
Cheryl L. Achterberg, PhD, Susan Wohlsdorf-Arendt, PhD, RD, Sandi Shepherd,
PhD.
Part 4: The Conduct of Observational and Experimental Research Studies
Ch 8: Analytic Nutrition Epidemiology
Monica E. Yamamoto, Dr.PH, RD, FADA
Ch 9: Designing, Managing, and Conducting a Clinical Nutrition Study
P.M. Kris-Etherton, PhD, RD
Ch 10: Interpretation and Utilization of Data from the National Nutrition
Monitoring and Related Research Program
Ronette R. Briefel, Dr.PH, RD
Part 5: Integrative and Translational Research
Ch 11: Meta-analysis in Nutrition Research
Judith Beto, PhD, RD
Ch 12: Research in Evidence-based Practice
Esther F. Myers, PhD, RD
Part 6: Evaluation and Assessment Methods in Research
Ch 13: Design and Use of Questionnaires in Research
Barbara E. Millen, PhD, RD
Ch 14: Dietary Assessment and Validation
Rachel K. Johnson, PhD, MPH, RD, Bethany A. Yon, MS, Jean Hankin, Dr.PH,
RD
Ch 15: Food Composition Data and Databases
Jean A.T. Pennington, PhD, RD
Ch 16: DRIs, ERAs, ULs, etc
Suzanne Murphy, PhD, RD
Ch 17: Biomarkers in Nutrition Research
Cheryl L Rock, PhD, RD, FADA, and Johanna W Lampe,PhD, RD
Ch 18: Culture and Research
Yvonne Bronner PhD, RD
Ch 19: Research Methods for Human Sensory System Analysis and
Food Evaluation
Richard D Mattes, PhD, RD and Beverly Cowart, PhD
Ch 20: Research Methods in Appetite Assessment
Richard D Mattes, PhD, RD
Part 7: Key Aspects of Research in Food, Nutrition, and Dietetics
Ch 21: Outcomes Research and Economic Analysis
Patricia L. Splett, PhD, RD, FADA
Ch 22: Research in Diet and Human Genetics
Cheryl L. Rock, PhD, RD, FADA
Ch 23: Behavioral Theory-based Research
Geoffrey W. Greene, PhD, RD
Ch 24: Research Methods for Dietary Supplements and Complementary
and Alternative Medicine
Cynthia Thomson PhD, RD and Leila Saldanha PhD, RD
Ch 25: Research in Foodservice Management
Bonnie L. Gerald, Ph.D DTR, Mary Cluskey, PhD, RD
Ch 26: Research Techniques Used to Support Marketing Management
Decisions
Kathleen Reidy, PhD, RD
Ch 27: Dietetics Education Research
Mary B. Gregoire, PhD, RD, FADA
Part 8: Application of Statistical Analysis in Nutrition and
Dietetics Research
Ch 28: Estimating Sample Size
Carol Boushey, PhD, MPH, RD, Jeffrey Harris, Dr.PH, RD, Barbara Bruemmer,
PhD, RD, and Sujata Archer, PhD, RD
Ch 29: Fundamentals of Statistical Analysis
Carol Boushey, PhD, MPH, RD, Jeffrey Harris, Dr.PH, RD, Barbara Bruemmer,
PhD, RD, and Sujata Archer, PhD, RD
Part 9: Presentation of Research Data
Ch 30: Techniques and Approaches for Presenting Research Findings
Judith A Driskell, PhD, RD, Elaine Monsen PhD, RD
Ch 31: Illustrating the Results of Research
Shortie McKinney, PhD, RD
Ch 32: Research Publications: The Perspectives of the Writer,
Reviewer, and Reader
Jeffrey Harris, Dr.PH, RD
CODA Applications of Research Practice
Ch 33: Bridging Research to Practice
Judith A. Gilbride, PhD, RD
Statistical concepts to emphasize and integrate throughout the book:
Research Hypotheses and Questions
Directional and Nondirectional Hypotheses (one-tailed and two-tailed tests)
Types of Variables
Scales of Measurement
Measures of Central Tendency
Measures of Dispersion
Types of Distributions and Central Limit Theorem
Skewness and Kurtosis
Descriptive Statistics
Research Designs (observational vs experimental)
Designs, and Cause and Effect
Inferential Statistics Decision-Making
Hypothesis Testing (steps)
Confidence Intervals
Z-scores
t-tests
ANOVA
Pearson’s Correlation
Regression
Nonparametric Tests
Odds Ratio
Relative Risk RatioIntent to Treat
Numbers Needed to Treat
Diagnostic Testing
Specificity and Sensitivity
Predictive Values
Likelihood Ratios
Advanced Statistical Tests
Multiple Regression
Logistic Regression
Cluster Analysis
Factor Analysis
Canonical Correlation
Discriminant Analysis
Log-Linear Modeling
Path Analysis
Interpretation of Statistical Tests
Computer Statistical Packages