# Measure variables at the highest level possible

## Don't discount your continuous variables!

Researchers

**lose valuable precision and accuracy in measurement when continuous variables are demoted to ordinal or categorical levels**. It is

**ALWAYS**better to take an actual numerical value with a "true zero" and analyze it using

**parametric statistics**. If there is a

**theoretical, conceptual, or empirical basis for pairing down continuous measures into lower levels of measurement**, then and only then should it be done. If you were a researcher and wanted to know the most precise and accurate measure possible of my age, which of the following is the best way to ask?

1. How many years old are you? (continuous)

2. How old are you? (circle one) 20-30 31-40 41-50 51-60 60+ (ordinal)

3. Are you above or below the age of 55? (categorical)

The continuous method will give you a stronger measure of age, which can then be broken down into separate ordinal or categorical levels,

**AT YOUR DISCRETION**. So, always measure at the continuous level if at all possible.

With this being said,

**PLEASE**realize that while we can go from continuous to ordinal and continuous levels of measurement,

**it is IMPOSSIBLE to change categorical and ordinal variable into a continuous level of measurement**.

Let's use a basic example:

**Gender**- 0 = male and 1 = female

Is there any way to convert this into a continuous variable? No.

Here is another example:

**How old are you? (circle one)**20-30 31-40 41-50 51-60 60+

Can you convert this into a continuous variable? No, again.

In conclusion,

**ALWAYS**try to measure your variables at a continuous level, if at all possible or feasible. They can be broken down into ordinal and categorical variables as needed. Also,

**REALIZE**that once you have decided to measure something at a categorical or ordinal level, it cannot be converted to continuous.