====== Study Classification ======

===== I. By Purpose =====
  * **Descriptive**: Describes characteristics or events.  
    _Example_: Prevalence of TBI in a population.
  * **Analytical**: Tests hypotheses and looks for associations.  
    _Example_: Smoking and glioblastoma correlation.
  * **Exploratory**: Investigates new or poorly understood areas.  
    _Example_: Unusual symptoms in post-COVID patients.
  * **Explanatory**: Attempts to explain mechanisms or causation.  
    _Example_: Role of IDH mutation in glioma prognosis.

===== II. By Design =====

==== A. Observational Studies ====

  * **Cross-sectional**: One-time snapshot.  
  * 
    _Pros_: Fast, low-cost.  
    
    _Cons_: No temporal or causal inference.
    
  * **Case-control**: Retrospective, comparing affected vs. unaffected.  
  * 
    _Pros_: Good for rare diseases.  
    
    _Cons_: Recall and selection bias.
    
  * **Cohort**: Follows exposed vs. unexposed over time.  
  * 
    _Pros_: Strong evidence for causality.  
    
    _Cons_: Expensive, long-term.
    
  * **Ecological**: Based on group/population data.  
  * 
    _Note_: Risk of ecological fallacy.

==== B. Experimental Studies ====
  * **Randomized Controlled Trial (RCT)**: Gold standard for intervention studies.
  * **Non-randomized Trial**: Allocation not random; higher risk of bias.
  * **Crossover Trial**: Same subjects receive all interventions in sequence.

===== III. By Timing =====
  * **Prospective**: Follows subjects into the future.
  * **Retrospective**: Uses past data to analyze outcomes.
  * **Ambispective**: Combines both.

===== IV. By Data Type =====
  * **Quantitative**: Numerical data (e.g., lab results, scores).
  * **Qualitative**: Textual/descriptive (e.g., interviews, observations).
  * **Mixed Methods**: Combination of both.