Analysis Plan
Purpose
Pre-register or outline the exact sequence of analytical steps.
Details
Objective: Model the probability of missed_appointment = 1.
Planned Steps: 1. Data Ingestion: Load data/derived/synthetic_healthcare_example.csv. 2. Descriptive Statistics: Calculate missingness and distributions for all predictors. 3. Bivariate Analysis: Chi-square tests for categorical predictors against the outcome; t-tests/Mann-Whitney for continuous predictors. 4. Multivariable Modeling: Fit a logistic regression model including all predefined covariates (age, lead_time_days, appointment_type, previous_missed, deprivation_quintile). 5. Assumptions Check: Assess multicollinearity using Variance Inflation Factor (VIF).
Awareness & Orientation: This analysis sequence reflects standard operating procedures for observational cohort data. No AI tools were needed to design these steps. We understand the limits of these methods for inferring causality.