{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jacquelineburos/miniconda3/envs/python3/lib/python3.5/site-packages/Cython/Distutils/old_build_ext.py:30: UserWarning: Cython.Distutils.old_build_ext does not properly handle dependencies and is deprecated.\n",
" \"Cython.Distutils.old_build_ext does not properly handle dependencies \"\n",
"/home/jacquelineburos/.local/lib/python3.5/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
" \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n",
"INFO:stancache.seed:Setting seed to 1245502385\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"%matplotlib inline\n",
"import random\n",
"random.seed(1100038344)\n",
"import survivalstan\n",
"import numpy as np\n",
"import pandas as pd\n",
"from stancache import stancache\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Simulate survival data "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In order to demonstrate the use of this model, we will first simulate some survival data using `survivalstan.sim.sim_data_exp_correlated`. As the name implies, this function simulates data assuming a constant hazard throughout the follow-up time period, which is consistent with the Exponential survival function.\n",
"\n",
"This function includes two simulated covariates by default (`age` and `sex`). We also simulate a situation where hazard is a function of the simulated value for `sex`. \n",
"\n",
"We also center the `age` variable since this will make it easier to interpret estimates of the baseline hazard.\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:stancache.stancache:sim_data_exp_correlated: cache_filename set to sim_data_exp_correlated.cached.N_100.censor_time_20.rate_coefs_54462717316.rate_form_1 + sex.pkl\n",
"INFO:stancache.stancache:sim_data_exp_correlated: Loading result from cache\n"
]
}
],
"source": [
"d = stancache.cached(\n",
" survivalstan.sim.sim_data_exp_correlated,\n",
" N=100,\n",
" censor_time=20,\n",
" rate_form='1 + sex',\n",
" rate_coefs=[-3, 0.5],\n",
")\n",
"d['age_centered'] = d['age'] - d['age'].mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Aside: In order to make this a more reproducible example, this code is using a file-caching function `stancache.cached` to wrap a function call to `survivalstan.sim.sim_data_exp_correlated`. *"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Explore simulated data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here is what these data look like - this is `per-subject` or `time-to-event` form:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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