What type of outcomes dose not involve continuous measures in meta-analysis?

Dichotomous outcomes refer to variables that can take on one of two possible values, often representing a condition or an event (e.g., success/failure, yes/no). In the context of meta-analysis, this type of outcome is significant because it allows for clear comparisons across studies. Each study can report the number of occurrences of the event versus non-occurrences, making it easy to aggregate results and calculate summary statistics through methods like risk ratios or odds ratios.

In contrast, continuous outcomes involve measurements that can take on any value within a range (e.g., weight, blood pressure), which requires different statistical methods for analysis and would not fall under the category of non-continuous measures. Qualitative outcomes pertain to non-numeric data and often involve subjective assessments that cannot be easily quantified into either dichotomous or continuous forms. Vote counting outcomes, while relying on non-continuous measures, also tend to summarize results in a manner that separates them from standard statistical practices typically applied to dichotomous measures.