Practical stats, part 1: understanding and reporting descriptive and bivariate analyses
Most research, especially in biomedical, behavioral and social sciences, involves statistical analysis of data. Manuscript editors and translators rarely have appropriate, recent training in statistics and data presentation and often have trouble figuring out what the results of statistical analyses mean. Moreover, many authors cannot help because they do not really understand the statistical analysis of their work either – they had a professional do it for them. This leaves an editor/translator out in the open with nothing but flashes of intuition to use for the job.
When people try to learn statistics on their own from a book, in most cases they give up after the introduction or, at best, after the first couple of chapters because learning statistics this way can be both difficult and boring. This workshop offers participants an alternative for developing an understanding of basic statistical concepts in a more digestible, guided way.
Developer and facilitator: Darko Hren
Purpose: To help manuscript editors and translators understand basic statistical concepts and terminology and provide them with elementary skills in reporting analyzed data.
Description: The workshop will be a mixture of information input and practical work. Each concept will first be explained and examples discussed. Practical exercises will be given along the way so we can put the knowledge into practice.
Structure: The workshop will consist of three modules giving a taste of the following:
- Descriptives, normal distribution and hypothesis testing: Participants will become familiar with basic descriptive indicators (mean ± standard deviation or standard error, confidence intervals, median and interquartile range, frequency vs percentage). They will learn when it is appropriate to use these indicators and what they mean. Elementary logic of sampling procedures, normal distribution and hypothesis testing will be explained.
- Group comparisons: What are independent and paired samples? Methods for comparing different types of data for different groups (i.e., normally distributed categorical vs continuous data: chi-square test, t test or ANOVA?; for nonnormally distributed ordinal or continuous data: Mann-Whitney test, Wilcoxon matched pairs test, Kruskal-Wallis test, Friedman's test? etc.) What are post-hoc tests? (And why use them? And how? And which one?) Practice in reporting results of testing group comparisons.
- Bivariate association: The difference between group comparisons and testing for associations. How we test for associations (for categorical data, chi-square test of association; for continuous normally distributed data, Pearson's r; for ordinal or continuous nonnormally distributed data, Spearman's rho). The relation between risk factors and outcome: absolute risk, relative risk, odds ratio. Practice in reporting results of testing bivariate associations.
Who should attend? Editors and translators working in disciplines that use statistics.
Outcome skills: After the workshop, participants will understand different approaches to data description and rationales for using them. They will understand methods for testing differences between two or more groups and for testing associations between two variables. They will also learn how the results of these analyses can be meaningfully presented.
Pre-meeting information: This workshop will be taught with a presumption that participants know and understand different scales of measurement and study designs through personal work experience or such as were discussed in the METM09 workshop Study designs in medical research: reporting structures and roles in knowledge-building, or the METM08 knowledge update Study designs in medical research: concepts and terminology.
To acquire or review a basic understanding (enough to follow the workshop) of scales of measurement read: http://allpsych.com/researchmethods/measurementscales.html or http://en.wikipedia.org/wiki/Level_of_measurement.
For a more detailed explanation read: http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stat_workshp/scale/scale_01.html.
To learn more about study designs start from http://en.wikipedia.org/wiki/Study_design and then follow the links to the different types of studies: randomized controlled trial, cohort study, case-control study, cross-sectional study.
About the facilitator: Darko Hren is an assistant professor at the University of Split Faculty of Humanities and Social Sciences, where he teaches social psychology, educational psychology, and basics of scientific methodology and communication. He was a statistical editor for the Croatian Medical Journal from 2002 until 2010. He gave earlier versions of his popular workshops on statistics at METM06, METM07, METM08, METM10, METM12 and METM14, and led the local organizing team for METM08 in Split.