CausalWizard
About
Features
Sign Up
Login
AI/ML Projects
Design a Project
Problem definition
Value proposition
Build a team
Data
Solution design
Evaluation
Adoption
Help
Features
Tutorials
Articles
Learn more
About (FAQ)
Contact
News
Data security
Fees
Legal
Ethics
Search for articles
Matching articles
Categories
Categories
Causal Wizard Concept
Graph
Data
Process
Causal Inference
Validation
Statistics
Variables
Study Design
Causal Effect
Independence
Method
Tutorial
A-Z list of articles
Academic papers
Adjustment (Frontdoor, Backdoor)
Assumptions
Average Treatment Effect (ATE)
Average Treatment Effect on the Treated (ATT)
Backdoor variable
Bias
Bootstrap validation
Cardinality
Causal Diagram
Causal Effect
Check (Verification and Identification)
Class Imbalance
Cohort
Common Cause (variable)
Conditional Average Treatment Effect (CATE)
Confidence Interval
Confounding / Confounder (Variable)
Control and Treated values for Treatment variable
Controlling for and Conditioning on a Variable
Correlation, Association and Causality
Counterfactual
Covariate Balance
Cycle (Graph)
Dataset (Tabular, Matrix)
Data types
Difference-in-differences (DID) (method)
Dimension (Data)
Directed Acyclic Graph (DAG)
Distribution (Data)
do-Calculus
Domain Knowledge
Double ML
Effect modifier (variable)
Estimand
Estimate
Estimation
Expected value
Experiment
Exploratory Data Analysis
Feature Importance (Model Explainer tools)
Fixed Effects models
Frontdoor variable
F-statistic
Generalization performance metrics
Graph (mathematics)
Identification
Independence (Samples and Variables)
Independent and Dependent variables
Inference (Statistics and Causal Inference)
Instrumental Variables (Method)
Intervention
Linearity and Non-linearity
Local Average Treatment Effect (LATE)
Machine Learning
Matching (method)
Mediation (process)
Model Selection
Model (Statistics and Machine Learning)
Observational data / studies
Observed / unobserved variable
Outcome (variable)
Panel Data format
Parameter
Parametric / Non-Parametric (Models)
Pending Results Queue
Placebo treatment refuter
Potential Outcomes Framework
Prior (Statistics)
Propensity Scores (Method)
p-values (Significance testing)
Random Common Cause Refuter
Randomized Controlled Trial (RCT)
Randomized Outcomes Refuter
Refutation
Refutation and Significance testing in DoWhy
Regression (method)
Research Question
Result
Sample (Sample Unit)
Software used in Causal Wizard
Standardisation and normalization
Study
Study Design and Method options
The Positivity Assumption
Treatment (variable)
Tutorial 1
Tutorial 2
Tutorial 3
Tutorial 4
Tutorial: Fixed Effects models
Validation
Variables
z-Statistic