In repeated measures data, the dependent variable is measured more than once for each subject. Usually, there is some independent variable (often called a within-subject factor) that changes with each measurement. And in longitudinal data, the dependent variable is measured at several time points for each subject, often over a relatively long period of time.
If you’ve ever run a one-way analysis of variance (ANOVA), you’re familiar with post-hoc tests. The ANOVA omnibus test only tells you whether any groups differ in their means. But if you want to explore which specific group mean is different from which, you need to follow up with a post-hoc test.
Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions and they become even more difficult to understand.
One big advantage of R is its breadth. If anything has been done in statistics, there is an R package that will do it. The problem is that sometimes there are four packages that will do it. This is big problem with R (and with Python for that matter).
When you need to compare a numeric outcome for two groups, what analysis do you think of first? Chances are, it’s the independent samples t-test. But that’s not the only, or always, the best option. In many situations, the Mann-Whitney U test is a better option. The non-parametric Mann-Whitney U test is also called the […]
Many data sets are challenging and time consuming to work with because the data are seldom in an optimal format.
So the question is what to do with your categorical variables. You have two choices, and each has advantages and disadvantages. The easiest is to put categorical variables in Fixed Factors. SPSS will dummy code those variables for you, which is quite convenient if your categorical variable has more than two categories. However, there are some defaults you need to be aware of that may or may not make this a good choice. SPSS always makes the reference group the one that comes last alphabetically. So if the values you input are strings, it will be the one that comes last. If those values are numbers, it will be the highest one.
Formatting Date Variables seems like it should be straightforward, but sadly, it’s not. If you are given data that includes dates, expect confusion. Dates can be represented in many different ways.
Moderated mediation, also known as Conditional Process Modeling, is great tool for understanding one type of complex relationship among variables.