Confusing Statistical Terms #3: Levels

热度 15已有 174 次阅读2010-11-15 23:38 |个人分类:基础科学|

Confusing Statistical Terms #3: Levels of a Factor in Multilevel Models Measured at a Nominal Level

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…..

http://www.analysisfactor.com/statchat/confusing-statistical-term-4-hierarchical-regression-vs-hierarchical-model/


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