This post is the third in the series describing the web-interface I created to administer a questionnaire with the Delphi method. In this post I describe the code used to give feedback to the participants in round 2 of the Delphi study on functional magnetic resonance imaging on tinnitus. If you are interested in the previous posts, this post describes the interface for round 1 whereas this post describes (the first part of) the interface for round 2.
Continue reading “Web-interface for Delphi Method III”
This post describes the web-interface I built for the second round of the Delphi method study on functional magnetic resonance imaging and tinnitus. In the second round, the experts who participated in the first round saw the responses that they gave to the first round side-by-side with the responses of all the other experts. As represented in the figure above, in round 2 the Delphi interface displayed one question and two bar plots showing the distribution of experts’ responses for the given question in round 1. To keep the post short and to the point, I divided the description of the interface for round 2 into two parts.
Continue reading “Web-interface for Delphi Method II”
I recently worked on a fun project at work. I developed a web-interface for administering a questionnaire using the Delphi method. The Delphi method aims to bring consensus on a given topic using a concept similar to ‘the wisdom of crowds‘.
Continue reading “Web-interface for Delphi method”
This post is an update on the previous post translating Byron and Wattenberg’s streamgraphs algorithm into R. Byron and Wattenberg’s algorithm produces beautiful streamgraphs with the synthetic data produced by their streams generator. However, the implementation yields an ugly streamgraph when applied to data which might not be as wiggly as the synthetic ones. In the attempts I made I got very peaky wiggles, not smoothed and irregular. In short the graphs did not transmit the idea of a stream, but of a blurry blob or a peaky primitive bat (the wooden club, not the animal, that would be cool!). In this post I bring-up some points to bear in mind when producing a streamgraph. Continue reading “Streamgraph in R [final]”
This is the third post on streamgraph in R. After a simple introduction on how to generate a streamgraphs and an example with actual data it was time for a more general implementation to the creation streamgraphs using R. Continue reading “Streamgraphs in base::R [e.III]”
This posts on multiple mediation on lavaan supplements the two previous ones (1 – introducing multiple mediator analysis with lavaan and 2 – showing an example analysis) by describing how to process lavaan’s output graphically. I discovered the handy package semPlot and I am very positive about it. I will make the example as reproducible as possible, so that each step can be repeated. Also, I am going to try to provide more explanation about the R commands I used because a friend pointed out that the description of the steps was sometimes a bit dry and abstract.
Continue reading “Plotting multiple mediation”
Until recently I did not have a practical application in which to use streamgraphs. In fact, I still find the visualisation complex to understand, abstract and a bit too artistic. While I recognise that the strength of streamgraphs is the display of all the time series’ values into one (possibly interactive) plot, the amount of data displayed is massive, with many streams and even more data points. Because of the amount of data displayed Continue reading “Streamgraphs in base::R [e.II]”