R Tutorial : Overview of the Measure Development Process

Want to learn more? Take the full course at https://learn.datacamp.com/courses/factor-analysis-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Now that you know how to conduct a single-factor EFA, you're ready to start thinking about how it fits into the process of developing a measure. When you're creating a measure of an unobservable variable or variables, you typically want to follow this process. Steps 1, 2, and 4 are theoretical and don't involve any coding so we won't spend much time on those. When you have determined what construct you want to measure, the first step is to write questions, or items, for your measure. Always write more items than you think you'll need since they probably won't all perform as well as you'd like. After you've got enough items developed, the next step is to collect pilot data from a representative sample to test the measure. These data will be used to examine your measure and see how it is functioning before you use it for real. You can think of the gcbs dataset as pilot data for these 15 items. Once you've got pilot data, the first step is to check out what the dataset looks like. To get a sense for your data, use the describe() function to see basic information about each of the items in the dataset. If you look at the first row of output, you can see in the column called n that item Q1 has 2,495 responses, a mean of 3.47, and a standard deviation of 1.46. You'll notice that the minimum and maximum are 0 and 5 for these items because they've been scored on a Likert scale. Now that you know some basic features of your dataset, you have to consider which analyses you want to run. If you want to both develop and confirm a theory of how items are related to underlying factors, you'll want to use both EFA and CFA on your dataset. In that case, you'll need to split the dataset - step 5 here. To do that, create a set of random indices, then use them to divi