- Definition?
- How to characterize them?
- Which software (free) is the best to analyze these outcome measures?
- How to combine Dichotomous outcome Continuous outcome (If data for the same outcome are presented in some studies as dichotomous data and in other studies as continuous data)?
Dichotomous: yes - no,
Continuous: absolutely sure, sure, rather sure, a little sure, I do not not, a little unsure, rather unsure, unsure, very unsure
There are some web calculators.
SPSS can analyze different data types including continuous or categorical. Continuous variables will result in the most powerful analysis whereas when the variable becomes discrete, categorical or binary the analysis is less powerful. Continuous data can be converted to categorical (yes/no) type whereas categorical data cannot be converted to continuous data unless you have the original raw data that helped you classify your observations into categories.
R (/Rstudio) is a great free stats program that can analyze either type of outcome.
https://www.rstudio.com/products/rstudio/download/
You can "bin" continuous data into dichotomous outcomes (i.e., 1 through 10 = high, 11 through 20 = low). But, generally it's better to use continuous data if you have a normal distribution because you're accounting for most of the variance, so if most of your data is continuous, I might stick to that. Depends on your research question and what your data looks like.
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