I’m happy to re-introduce a working e-text for my PSYC 3950: Research Methods and Statistics III class. There will be continued updates.

The book can be found here: https://insightsandanalyses.netlify.app

Standard cut-offs are not recommended when determining a suitable effect size for a power analysis. Indeed, the ‘meaningfulness’ of an effect size will depend on some subjective elements. That is, a ‘small’ effect may have drastic implications in certain contexts, while ‘large’ effects may have little to no implications in other contexts. A recent publication has provided a practical example to help differentiate a statistically versus a clinical meaningful effect size.

Shiny applications offer a fantastic way to produce interactive web applications. Unsurprisingly, there are abundant R packages built specifically for Shiny to facilitate ‘telling your data story’. For example, I often use the pickerInput() function from the shinyWidgets package, which is more aesthetic and has built-in ‘Select All/None’ buttons compared to the base checkboxGroupInput(). pickerInput(inputId = 'picker', label = 'Please choose your options', choices = c("Plot", "Text", "Analysis"), multiple = T, options = list(`actions-box` = TRUE)) Please choose your options Plot Text Analysis This basic interface allows users to select any combination of selections.