It struck me today in answering a question that statisticians have not been very helpful to those trying to learn statistics in the way they name statistical terms.
I can think of other examples (how many totally different concepts does alpha refer to in statistics?), but the term I was using today was levels.
Specifically, there are Multilevel models with two or more sources of random variation. A two level model has two sources of random variation, and can have predictors at each level. A common example is where students are sampled within schools. Predictors can be measured at the student level (eg. gender, SES, age) or the school level (enrollment, % who go on to college). The dependent variable has variation from student to student (level 1) and from school to school (level 2).
If a predictor is a fixed factor (meaning it is a categorical predictor), it can have two or more levels, meaning categories. In ANOVA, factors (categorical independent variables) have 2 or more levels (2 or more categories).
Then we get to levels of measurement: nominal, ordinal, interval, ratio. These levels refer to how much information a variable contains. Does it indicate a category, indicate a quantity, etc?
So, a factor with 3 levels that is measured at level 2 of a model has a nominal level of measurement.
What, you’re not following me? I wonder why…..
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Confusing Statistical Terms #1: Independent Variable
Confusing Statistical Terms #2: Alpha and Beta
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