I have a retrospective dataset of patients treated with a certain drug (treatment, $n=46$) or with placebo (control $n=96$). The stored variables are age, sex, stage of disease. I want to assess the effect of treatment on overall survival with propensity score. Here are the steps I followed:
- I calculated propensity score with a binary logistic regression model using treatment as dependent variable and age, sex, stage as covariates.
- I used fuzzy matching to create a 1:1 matching with 0.05 tolerance.
- I deleted the unmatched cases and obtained a dataset of 46*2 cases (46 treated, 46 controls).
- I used a Cox proportional regression model using propensity score and treatment as covariates.
Is my procedure correct? I'm using SPSSv19.