pydts 0.2.0

Discrete time survival analysis with competing risks

Discrete Time Survival Analysis

A Python package for discrete time survival data analysis with competing risks.

Tomer Meir, Rom Gutman, Malka Gorfine 2022

Documentation

Installation

pip install pydts

Quick Start

from pydts.fitters import TwoStagesFitter
from pydts.examples_utils.generate_simulations_data import generate_quick_start_df
from sklearn.model_selection import train_test_split

patients_df = generate_quick_start_df(n_patients=10000, n_cov=5, d_times=30, j_events=2, pid_col='pid', seed=0)
train_df, test_df = train_test_split(patients_df, test_size=0.25)

fitter = TwoStagesFitter()
fitter.fit(df=train_df.drop(['C', 'T'], axis=1))
fitter.print_summary()

Other Examples

1. Simple Example
2. Hospital Length of Stay Simulation Example