Study design

An Introduction to Repeated Measures Designs

May 23rd, 2024 by

There are many designs that could be considered Repeated Measures design, and they all have one key feature: you measure the outcome variableStage 2 for each subject on several occasions, treatments, or locations.

Understanding this design is important for avoiding analysis mistakes. For example, you can’t treat multiple observations on the same subject as independent observations.


Suppose that you recruit 10 subjects (more…)

Six Easy Ways to Complicate Your Analysis

July 13th, 2021 by

It’s easy to make things complex without meaning to. Especially in statistical analysis.

Sometimes that complexity is unavoidable. You have ethical and practical constraints on your study design and variable measurement. Or the data just don’t behave as you expected. Or the only research question of interest is one that demands many variables.

But sometimes it isn’t. Seemingly innocuous decisions lead to complicated analyses. These decisions occur early in the design, research questions, or variable choice.


Member Training: Writing Study Design and Statistical Analysis Plans

May 3rd, 2021 by

One component often overlooked in the ‘Define & Design’ phase of a study, is writing the analysis plan. The statistical analysis plan integrates a lot of information about the study including the research question, study design, variables and data used, and the type of statistical analysis that will be conducted.


Types of Study Designs in Health Research: The Evidence Hierarchy

March 24th, 2021 by

by Danielle Bodicoat

Statistics can tell us a lot about our data, but it’s also important to consider where the underlying data came from when interpreting results, whether they’re our own or somebody else’s.

Not all evidence is created equally, and we should place more trust in some types of evidence than others.


The Right Analysis or the Best Analysis? What to Do When You Can’t Run the Ideal Analysis 

March 9th, 2020 by

One activity in data analysis that can seem impossible is the quest to find the right analysis. I applaud the conscientiousness and integrity that underlies this quest.

The problem: in many data situations there isn’t one right analysis.


Eight Data Analysis Skills Every Analyst Needs

October 24th, 2019 by

It’s easy to think that if you just knew statistics better, data analysis wouldn’t be so hard.

It’s true that more statistical knowledge is always helpful. But I’ve found that statistical knowledge is only part of the story.

Another key part is developing data analysis skills. These skills apply to all analyses. It doesn’t matter which statistical method or software you’re using. So even if you never need any statistical analysis harder than a t-test, developing these skills will make your job easier.