- #BAYESIAN IN COMPREHENSIVE META ANALYSIS HOW TO#
- #BAYESIAN IN COMPREHENSIVE META ANALYSIS SOFTWARE#
- #BAYESIAN IN COMPREHENSIVE META ANALYSIS TV#
So for example, let’s say that I invented a new drug to lower blood pressure. When you ask a statistician that question, what the statistician hears is “I want to know the effect size.” According to Wikipedia, “in statistics, an effect size is a quantitative measure of the magnitude of a phenomenon.” ( ). What you want to know is if the treatment matters in the real world. Adding more participants to a study doesn’t make a treatment more or less effective. So, in general, as N goes up, the p-value goes down, holding everything else (e.g., alpha, effect size) constant.īut this doesn’t really answer your question. And most statisticians realize that this p-value is closely related to the number of participants, which is usually called N. In statistics (at least as it is practiced today) “statistical significance” means that the p-value associated with the test statistic is less than.
Now to a statistician, this is not surprising at all. So you do this, but then you notice something that seems a little odd: the greater the number of participants in a study, the more likely the study was to find a significant result. Now what do you do? You may decide that you are going to find all of the studies on this research question and count up how many found significant results and how many did not. You find that some of the studies replicated the results while others did not (i.e., failure to replicate results). So let’s say that this topic is something that you really care about, and you wait to hear more results from the replication studies. Almost always, there is a quote from one of the study’s authors saying that “this research needs to be replicated with more subjects before anyone should act on the results.” And we all nod our heads, because we know that replication is an important part of the foundation of the scientific method. Some new drug, or treatment, or something, has been shown to do something.
#BAYESIAN IN COMPREHENSIVE META ANALYSIS TV#
Here’s an experience we can all relate to: you read about a study on your favorite news website, or hear about it on TV or the radio. Remember that this is a brief introduction to this topic, so we will only briefly touch on many important topics that might be worthy of an entire workshop unto themselves. I assume that you are familiar with basic descriptive statistics, such as means and standard deviations what an odds ratio is what heterogeneity means. Will not cover any of the more advanced topics, such as multiple imputation of missing data or multilevel meta-analysis Assumptions
#BAYESIAN IN COMPREHENSIVE META ANALYSIS HOW TO#
How to access and/or use electronic databases
#BAYESIAN IN COMPREHENSIVE META ANALYSIS SOFTWARE#
This is not an introduction to the use of Stata software This is not a hands-on workshop we will not be running the commands today Resources for further information What not to expect How to run a meta-analysis and interpret the resultsĪ brief discussion of the different types of biases that may compromise the results of a meta-analysis Information on how to collect data for a systematic review and/or meta-analysis Definition of systematic review and meta-analysis