This is a website associated with a very nice book on the pragmatic aspects of running a clinical trial. I came across this site because I was looking for a simple example of a letter to doctors asking them to help recruit patients for a clinical trial. This was in an appendix along with other nice examples of things like case report forms, serious adverse event forms, HIPAA consent template, etc. You can download a free PDF version of this book or you can buy a paper copy. Continue reading
The Teaching of Statistics in the Health Sciences (TSHS) section of the American Statistical Association has put together a set of resources for teachers including several very interesting datasets. some of the resources are open to anyone, but others require a registration. Continue reading
I’m digging into some of the complexities of i2b2, especially in the concept path that shows how a particular piece of information in the electronic health record fits into the hierarchy. A colleague pointed me to this nice online document that explains some of this hierarchy. Continue reading
As a community, we statisticians have known for a long time that we do not teach that introductory level class in Statistics as well as we should. This guideline list the things and ways we SHOULD teach as well as things that we might think about leaving out. Continue reading
If you are writing a research grant, there are a lot of statistical issues that you need to consider. This guide, prepared by the American Statistical Association, highlights three areas: framing the problem, designing the study, and specifying the data analysis plan. It doesn’t talk enough about data management, but otherwise it is an excellent resource. Continue reading
I’m somewhat new to geocoding. One of the first things you might be interested in, if you have geographic data, is an indicator as to whether a certain address, zip code, or county is urban or rural. This is actually quite a complex topic. This paper outlines some of the basic systems to classifying a location as urban, rural, or something in between (e.g., suburban). Continue reading
This is a nice compilation of issues that you should be concerned. The examples are mostly from things that interest Google, but you will find this advice itself is useful no matter what type of data you work with. The advice is split into three broad categories: technical (e.g., look at your distributions), process (e.g., separate validation, description, and evaluation), and communication (e.g., data analysis starts with questions, not data or a technique). Continue reading
I’m an experienced R programmer trying to learn a little about SQL. One of my good friends who lives totally in the database world (I call her the Teradata Queen), shared a link to a blog post at SQLServerCentral about using R. Microsoft is including R in its SQL Server distribution, so this is an opportunity for a lot of interesting work combining the data manipulation power of SQL Server with the data analysis power of R. Anyway, the blog post explains some of the cost and performance issues associated with R scripts running on a SQL Server CPU. Continue reading
When evaluating a series of research articles, you often have to assess the quality of the individual papers based on the type of blinding, for example. What do you do if the paper does not discuss these items? I have usually advocated a “no news is bad news policy.” If a paper does not mention blinding, assume that no blinding was done. It seems reasonable, but the paper by Mhaskar et al provides empirical evidence that sometimes authors leave out information that would strengthen the credibility of their study. A similar paper is at https://www.ncbi.nlm.nih.gov/pubmed/22424985 Continue reading
This article is a synthesis of a panel discussion at the 2014 Joint Statistical Meetings on the flipped classroom. The article discusses it solely from the perspective of Biostatistics classes, though they offer some references for the flipped classroom in a more general setting. A flipped classroom is a course where the traditional didactic lectures are recorded and watched at home and the homework that would normally be done at home is done instead in the classroom. This homework in a Biostatistics class often takes the form of active learning in small groups, such as critiquing published research studies or conducting analyses on real world data sets. The key component, according to the authors, is the in class interactions during these assignments. Students learn from each other as they work in groups.
Now you could do active learning in a traditional course format. What a flipped classroom does is increases the emphasis and the amount of time spent in active learning.
The common theme of the paper is that the flipped classroom has been successfully applied in a variety of settings. It is not a “one size fits all” approach, but rather can be adapted to the needs of the particular class. Some students may not like the flipped classroom format, and you shouldn’t underestimate the amount of time needed to prepare the videotaped lectures (one rule of thumb is ten hours of work for every hour of video). Still the student reactions and the instructors perceptions of the flipped classroom are generally positive. Continue reading