## Meta-Analysis Course

Video Series

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## How the Course Works

*Videos*

There are 13 video-based lessons in this course. Work through each lesson at your own pace.

*Discussion board*

Post questions to the discussion board. I will post answers using text or custom-made videos.

*Public zoom meetings*

We will hold group zoom meetings several times a week.

*Private zoom meetings*

I will also host private zoom meetings by appointment.

## At the conclusion of this course, you will understand:

Basic issues in meta-analysis- How to choose a statistical model
- The meaning of the summary effect size
- How we can (and cannot) generalize from the meta-analysis to other populations
- How to choose an effect size index
- How to choose between narrow vs. broad inclusion criteria for selecting studies

- To enter data
- To run an analysis
- To see how much weight is assigned to each study
- To perform a sensitivity analysis
- To compute prediction intervals
- To create a high-resolution plot

- How to interpret each of the statistics associated with heterogeneity
- What I-squared tells us (and does not tell us)
- How to compute a prediction interval
- How to plot the distribution of true effects
- How to understand the difference between a confidence interval and a prediction interval

How to avoid common mistakes

- Avoid mistakes in choosing a statistical model
- Understand limitations of the fixed-effect analysis
- Understand limitations of the random-effects analysis
- Understand the common misinterpretation of the I-squared statistic

## Is this course too basic for me?

Probably not. While the course is geared to researchers, statisticians who attend our workshops invariably report that they found the course well worth their time. The overwhelming majority of meta-analyses contain some serious mistakes. You will learn what these mistakes are and how to avoid them in your own work.

## Is the course too advanced for me?

Probably not. The course assumes only basic knowledge of research techniques and no knowledge of meta-analysis. The course is intended for researchers rather than statisticians. I focus on a conceptual approach to each issue and use practical examples from published analyses. Statistical formulas are typically addressed separately and explained in a way that focuses on the logic rather than the math.

## Can I see a sample video?

To get a sense of the course, watch this video on heterogeneity. This should give you a sense of how the course works.## Do I need to be online at any specific time?

No. The videos are available to watch at your leisure.

The zoom sessions will be scheduled at various times of the day/night

so you can attend any that work for you.

The zoom sessions will be scheduled at various times of the day/night so you can attend any that work for you.

You can post questions at your convenience. We will generally post a response within 1 business day. In some cases this will be written, and in some cases I will create a video in response. If the issue calls for an extended discussion, I will set up a private zoom based on your time zone.

## How much time will I spend on this course?

To work through the videos, and carry out all the analyses demonstrated in the videos, will take roughly 15 hours. To get the most out of this course I recommend that you also participate in some of the zoom meetings, which will take as much time as you’d like. You may also want to use your own data sets to practice the concepts explained in the videos. If you have questions, we can address these in written correspondence or via zoom.

The subscription runs for the number of months you select. This allows you to complete the course and apply it to your own work. Then, you can choose to re-watch the videos and ask additional questions.

## May I ask questions about my own data?

I assume that some participants will want to apply the concepts to their own data and will have questions when they do so. I encourage that and will be happy to address these questions. I try to address general questions in the group chats and questions of a more specific nature in private chats.

I am happy to address questions about your analysis (for example “What does it mean that I-squared is 80% despite the fact that the effects all seem to be consistent” or “The journal said that we should apply this statistical model – how should we respond?”). However, I am not set up to review entire papers (for example, “Could you critique this paper?”). To review entire papers properly requires an amount of time that would not be possible.

## What This Course Does Not Cover

This course covers basic meta-analysis. The specific topics are detailed in the table of contents. Over the next few months we will be adding intermediate and advanced courses in meta-analysis. Persons who attend the basic course will be offered a discounted rate for those courses.

The course does not cover network meta-analysis, meta-analysis of diagnostic tests, or Bayesian methods.

## The Instructor

The course is taught by Michael Borenstein. Dr. Borenstein is the co-author (with Larry Hedges, Julian Higgins, and Hannah Rothstein) of the text Introduction to Meta-Analysis. He is also the author of the text Common Mistakes in Meta-Analysis and How to Avoid Them. Dr. Borenstein has been teaching workshops on meta-analysis for fifteen years. These include invited workshops at the FDA, CDC, NIH, and various pharmaceutical companies and universities. It also includes workshops on meta-analysis open to the public in the United States, the UK, Australia, Singapore, Israel, and Switzerland. These workshops have been attended by some two thousand people. He regularly reviews papers for journals in the fields of medicine and social science.

## The Software

The goal of this course is to teach meta-analysis, rather than primarily teaching how to use any specific program. However, I will be using the software Comprehensive Meta-Analysis (CMA) in course examples. Course registration includes free access to the program for one month.

## The Text

There is no required text. However, the course is based on the following texts, which can be ordered on Amazon:

- Introduction to Meta-Analysis (Borenstein, Hedges, Higgins and Rothstein)
- Common Mistakes in Meta-Analysis and How to Avoid Them (Borenstein)

## What if I try the course and it’s not what I need?

Cancel within one week for a full refund.

## What have others said about this course?

Click here to see comments from the in-person courses.

## Other Questions

Please e-mail me with any questions. My e-mail is biostat100@gmail.com.

## What is the cost?

**All options include:**

Unlimited access to videos (~10 hours).

Unlimited access to Zoom discussions.

Unlimited access for questions related to the course.

If you participated in a prior workshop by Michael Borenstein, you will receive a 20% discount on the basic courses. Click here for 3 months of access and here for 1 month of access.

*The course start date is the day you register. Access is available immediately after purchase.*

**If you wish to postpone the start date please contact us to make special arrangements prior to purchasing.**Looking to pre-purchase the advanced course? Contact us for help.

#### Video Series

Table of Contents

Modules marked with an asterisk (*) should not be skipped. These contain information that is important for the modules that follow.

#### Introduction

###### Introduction

*10 Minutes*

###### Cannon Analysis

*61 Minutes*

###### Tamiflu Symptom Relief

*50 Minutes*

###### How a Meta-Analysis Works

*21 Minutes*

###### Fixed Effect vs. Random Effects *

*74 Minutes*

###### Effect Sizes

*58 Minutes*

###### Effect Size vs. P-value

*27 Minutes*

###### What Studies to Include

*27 Minutes*

#### Heterogeneity

###### Heterogeneity *

*88 Minutes*

In this module, I start by reviewing how we think about heterogeneity in a primary study. Then, I show that the same ideas apply in a meta-analysis. In a section called “Forget what you know,” I show that most of what researchers “know” about heterogeneity is wrong. Statistics such as the Q-value, the p-value, I-squared and Tau-squared, do not tell us how much the effect size varies. Then, I discuss the statistics that do actually tell us how much the effect size varies – these include Tau (in some cases) and the prediction interval. I show how to compute and report these values. I then discuss how to use the heterogeneity, in conjunction with the mean effect size, to consider the clinical utility of the treatment or (more generally) the substantive implications of the findings. I also discuss what the other statistics do tell us. The module ends with an appendix that shows how the various statistics are related to each other, using clear and intelligent graphics.

###### ADHD

*46 Minutes*

###### I-squared

*64 Minutes*

If you’ve never heard of I-squared before this course, you may want to skip this module. But if you have been working with I-squared, you are likely to find this module enlightening. A few years ago I was teaching this workshop in London, and Julian Higgins (who created the I-squared statistic with Simon Thompson) was kind enough to drop in at the workshop and explain to the participants that what I said about I-squared is correct. This module includes a video clip of Julian’s remarks to the group.

###### Prediction Intervals

*33 Minutes*

###### Viagra

*52 Minutes*

###### PTSD

*37 Minutes*