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Proportional hazard assumption.ipynb
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Proportional hazard assumption.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'\n",
"\n",
"from matplotlib import pyplot as plt\n",
"from lifelines import CoxPHFitter\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Testing the proportional hazard assumptions\n",
"\n",
"This Jupyter notebook is a small tutorial on how to test and fix proportional hazard problems. An important question to first ask is: [_do I need to care about the proportional hazard assumption?_](#Do-I-need-to-care-about-the-proportional-hazard-assumption?) - often the answer is no. \n",
"\n",
"The proportional hazard assumption is that _all_ individuals have the same hazard function, but a unique scaling factor infront. So the _shape_ of the hazard function is the same for all individuals, and only a scalar multiple changes per individual. \n",
"\n",
"$$h_i(t) = a_i h(t)$$\n",
"\n",
"At the core of the assumption is that $a_i$ is not time varying, that is, $a_i(t) = a_i$. Further more, if we take the ratio of this with another subject (called the hazard ratio): \n",
"\n",
"$$\\frac{h_i(t)}{h_j(t)} = \\frac{a_i h(t)}{a_j h(t)} = \\frac{a_i}{a_j}$$\n",
"\n",
"is constant for all $t$. In this tutorial we will test this non-time varying assumption, and look at ways to handle violations. \n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<lifelines.CoxPHFitter: fitted with 432 total observations, 318 right-censored observations>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from lifelines.datasets import load_rossi\n",
"rossi = load_rossi()\n",
"cph = CoxPHFitter()\n",
"\n",
"cph.fit(rossi, 'week', 'arrest')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <tbody>\n",
" <tr>\n",
" <th>model</th>\n",
" <td>lifelines.CoxPHFitter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>duration col</th>\n",
" <td>'week'</td>\n",
" </tr>\n",
" <tr>\n",
" <th>event col</th>\n",
" <td>'arrest'</td>\n",
" </tr>\n",
" <tr>\n",
" <th>baseline estimation</th>\n",
" <td>breslow</td>\n",
" </tr>\n",
" <tr>\n",
" <th>number of observations</th>\n",
" <td>432</td>\n",
" </tr>\n",
" <tr>\n",
" <th>number of events observed</th>\n",
" <td>114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>partial log-likelihood</th>\n",
" <td>-658.748</td>\n",
" </tr>\n",
" <tr>\n",
" <th>time fit was run</th>\n",
" <td>2020-07-26 22:15:39 UTC</td>\n",
" </tr>\n",
" <tr>\n",
" <th>model</th>\n",
" <td>untransformed variables</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div><table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>coef</th>\n",
" <th>exp(coef)</th>\n",
" <th>se(coef)</th>\n",
" <th>coef lower 95%</th>\n",
" <th>coef upper 95%</th>\n",
" <th>exp(coef) lower 95%</th>\n",
" <th>exp(coef) upper 95%</th>\n",
" <th>z</th>\n",
" <th>p</th>\n",
" <th>-log2(p)</th>\n",
" </tr>\n",
" <tr>\n",
" <th>covariate</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>fin</th>\n",
" <td>-0.379</td>\n",
" <td>0.684</td>\n",
" <td>0.191</td>\n",
" <td>-0.755</td>\n",
" <td>-0.004</td>\n",
" <td>0.470</td>\n",
" <td>0.996</td>\n",
" <td>-1.983</td>\n",
" <td>0.047</td>\n",
" <td>4.398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>age</th>\n",
" <td>-0.057</td>\n",
" <td>0.944</td>\n",
" <td>0.022</td>\n",
" <td>-0.101</td>\n",
" <td>-0.014</td>\n",
" <td>0.904</td>\n",
" <td>0.986</td>\n",
" <td>-2.611</td>\n",
" <td>0.009</td>\n",
" <td>6.791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>race</th>\n",
" <td>0.314</td>\n",
" <td>1.369</td>\n",
" <td>0.308</td>\n",
" <td>-0.290</td>\n",
" <td>0.918</td>\n",
" <td>0.748</td>\n",
" <td>2.503</td>\n",
" <td>1.019</td>\n",
" <td>0.308</td>\n",
" <td>1.698</td>\n",
" </tr>\n",
" <tr>\n",
" <th>wexp</th>\n",
" <td>-0.150</td>\n",
" <td>0.861</td>\n",
" <td>0.212</td>\n",
" <td>-0.566</td>\n",
" <td>0.266</td>\n",
" <td>0.568</td>\n",
" <td>1.305</td>\n",
" <td>-0.706</td>\n",
" <td>0.480</td>\n",
" <td>1.058</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mar</th>\n",
" <td>-0.434</td>\n",
" <td>0.648</td>\n",
" <td>0.382</td>\n",
" <td>-1.182</td>\n",
" <td>0.315</td>\n",
" <td>0.307</td>\n",
" <td>1.370</td>\n",
" <td>-1.136</td>\n",
" <td>0.256</td>\n",
" <td>1.965</td>\n",
" </tr>\n",
" <tr>\n",
" <th>paro</th>\n",
" <td>-0.085</td>\n",
" <td>0.919</td>\n",
" <td>0.196</td>\n",
" <td>-0.469</td>\n",
" <td>0.299</td>\n",
" <td>0.626</td>\n",
" <td>1.348</td>\n",
" <td>-0.434</td>\n",
" <td>0.665</td>\n",
" <td>0.589</td>\n",
" </tr>\n",
" <tr>\n",
" <th>prio</th>\n",
" <td>0.091</td>\n",
" <td>1.096</td>\n",
" <td>0.029</td>\n",
" <td>0.035</td>\n",
" <td>0.148</td>\n",
" <td>1.036</td>\n",
" <td>1.159</td>\n",
" <td>3.194</td>\n",
" <td>0.001</td>\n",
" <td>9.476</td>\n",
" </tr>\n",
" </tbody>\n",
"</table><div>\n",
"<style scoped>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <tbody>\n",
" <tr>\n",
" <th>Concordance</th>\n",
" <td>0.640</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Partial AIC</th>\n",
" <td>1331.495</td>\n",
" </tr>\n",
" <tr>\n",
" <th>log-likelihood ratio test</th>\n",
" <td>33.266 on 7 df</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-log2(p) of ll-ratio test</th>\n",
" <td>15.370</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/latex": [
"\\begin{tabular}{lrrrrrrrrrr}\n",
"\\toprule\n",
"{} & coef & exp(coef) & se(coef) & coef lower 95\\% & coef upper 95\\% & exp(coef) lower 95\\% & exp(coef) upper 95\\% & z & p & -log2(p) \\\\\n",
"covariate & & & & & & & & & & \\\\\n",
"\\midrule\n",
"fin & -0.379 & 0.684 & 0.191 & -0.755 & -0.004 & 0.470 & 0.996 & -1.983 & 0.047 & 4.398 \\\\\n",
"age & -0.057 & 0.944 & 0.022 & -0.101 & -0.014 & 0.904 & 0.986 & -2.611 & 0.009 & 6.791 \\\\\n",
"race & 0.314 & 1.369 & 0.308 & -0.290 & 0.918 & 0.748 & 2.503 & 1.019 & 0.308 & 1.698 \\\\\n",
"wexp & -0.150 & 0.861 & 0.212 & -0.566 & 0.266 & 0.568 & 1.305 & -0.706 & 0.480 & 1.058 \\\\\n",
"mar & -0.434 & 0.648 & 0.382 & -1.182 & 0.315 & 0.307 & 1.370 & -1.136 & 0.256 & 1.965 \\\\\n",
"paro & -0.085 & 0.919 & 0.196 & -0.469 & 0.299 & 0.626 & 1.348 & -0.434 & 0.665 & 0.589 \\\\\n",
"prio & 0.091 & 1.096 & 0.029 & 0.035 & 0.148 & 1.036 & 1.159 & 3.194 & 0.001 & 9.476 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n"
],
"text/plain": [
"<lifelines.CoxPHFitter: fitted with 432 total observations, 318 right-censored observations>\n",
" duration col = 'week'\n",
" event col = 'arrest'\n",
" baseline estimation = breslow\n",
" number of observations = 432\n",
"number of events observed = 114\n",
" partial log-likelihood = -658.748\n",
" time fit was run = 2020-07-26 22:15:39 UTC\n",
" model = untransformed variables\n",
"\n",
"---\n",
" coef exp(coef) se(coef) coef lower 95% coef upper 95% exp(coef) lower 95% exp(coef) upper 95%\n",
"covariate \n",
"fin -0.379 0.684 0.191 -0.755 -0.004 0.470 0.996\n",
"age -0.057 0.944 0.022 -0.101 -0.014 0.904 0.986\n",
"race 0.314 1.369 0.308 -0.290 0.918 0.748 2.503\n",
"wexp -0.150 0.861 0.212 -0.566 0.266 0.568 1.305\n",
"mar -0.434 0.648 0.382 -1.182 0.315 0.307 1.370\n",
"paro -0.085 0.919 0.196 -0.469 0.299 0.626 1.348\n",
"prio 0.091 1.096 0.029 0.035 0.148 1.036 1.159\n",
" z p -log2(p)\n",
"covariate \n",
"fin -1.983 0.047 4.398\n",
"age -2.611 0.009 6.791\n",
"race 1.019 0.308 1.698\n",
"wexp -0.706 0.480 1.058\n",
"mar -1.136 0.256 1.965\n",
"paro -0.434 0.665 0.589\n",
"prio 3.194 0.001 9.476\n",
"---\n",
"Concordance = 0.640\n",
"Partial AIC = 1331.495\n",
"log-likelihood ratio test = 33.266 on 7 df\n",
"-log2(p) of ll-ratio test = 15.370"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cph.print_summary(model=\"untransformed variables\", decimals=3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checking assumptions with `check_assumptions`\n",
"\n",
"New to lifelines 0.16.0 is the `CoxPHFitter.check_assumptions` method. This method will compute statistics that check the proportional hazard assumption, produce plots to check assumptions, and more. Also included is an option to display advice to the console. Here's a breakdown of each information displayed:\n",
"\n",
" - Presented first are the results of a statistical test to test for any time-varying coefficients. A time-varying coefficient imply a covariate's influence _relative to the baseline_ changes over time. This implies a violation of the proportional hazard assumption. For each variable, we transform _time_ four times (these are common transformations of time to perform). If _lifelines_ rejects the null (that is, _lifelines_ rejects that the coefficient is not time-varying), we report this to the user.\n",
" - Some advice is presented on how to correct the proportional hazard violation based on some summary statistics of the variable. \n",
" - As a compliment to the above statistical test, if the option `show_plots = True` is specified, visual plots of the the _scaled Schoenfeld residuals_ are presented for all covariates against the four time transformations. A fitted lowess is also presented, along with 10 bootstrapped lowess lines (as an approximation to the confidence interval of the original lowess line). Ideally, this lowess line is constant (flat). Deviations away from the constant line are violations of the PH assumption. \n",
" \n",
"#### Why the _scaled Schoenfeld residuals_?\n",
" \n",
"This section can be skipped on first read. Let $s_{t,j}$ denote the scaled Schoenfeld residuals of variable $j$ at time $t$, $\\hat{\\beta_j}$ denote the maximum-likelihood estimate of the $j$th variable, and $\\beta_j(t)$ a time-varying coefficient in (fictional) alternative model that allows for time-varying coefficients. Therneau and Grambsch showed that. \n",
"\n",
"$$E[s_{t,j}] + \\hat{\\beta_j} = \\beta_j(t)$$\n",
"\n",
"The proportional hazard assumption implies that $\\hat{\\beta_j} = \\beta_j(t)$, hence $E[s_{t,j}] = 0$. This is what the above proportional hazard test is testing. Visually, plotting $s_{t,j}$ over time (or some transform of time), is a good way to see violations of $E[s_{t,j}] = 0$, along with the statisical test. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The ``p_value_threshold`` is set at 0.05. Even under the null hypothesis of no violations, some\n",
"covariates will be below the threshold by chance. This is compounded when there are many covariates.\n",
"Similarly, when there are lots of observations, even minor deviances from the proportional hazard\n",
"assumption will be flagged.\n",
"\n",
"With that in mind, it's best to use a combination of statistical tests and visual tests to determine\n",
"the most serious violations. Produce visual plots using ``check_assumptions(..., show_plots=True)``\n",
"and looking for non-constant lines. See link [A] below for a full example.\n",
"\n"
]
},
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" <td>1</td>\n",
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" <td><lifelines.CoxPHFitter: fitted with 432 total ...</td>\n",
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" <th rowspan=\"2\" valign=\"top\">age</th>\n",
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" <td>11.03</td>\n",
" <td><0.005</td>\n",
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" <td>0.02</td>\n",
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" <th>rank</th>\n",
" <td>0.71</td>\n",
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" <td>1.44</td>\n",
" <td>0.23</td>\n",
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" <td>1.43</td>\n",
" <td>0.23</td>\n",
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"\n",
"\n",
"1. Variable 'age' failed the non-proportional test: p-value is 0.0007.\n",
"\n",
" Advice 1: the functional form of the variable 'age' might be incorrect. That is, there may be\n",
"non-linear terms missing. The proportional hazard test used is very sensitive to incorrect\n",
"functional forms. See documentation in link [D] below on how to specify a functional form.\n",
"\n",
" Advice 2: try binning the variable 'age' using pd.cut, and then specify it in `strata=['age',\n",
"...]` in the call in `.fit`. See documentation in link [B] below.\n",
"\n",
" Advice 3: try adding an interaction term with your time variable. See documentation in link [C]\n",
"below.\n",
"\n",
"\n",
"2. Variable 'wexp' failed the non-proportional test: p-value is 0.0063.\n",
"\n",
" Advice: with so few unique values (only 2), you can include `strata=['wexp', ...]` in the call in\n",
"`.fit`. See documentation in link [E] below.\n",
"\n",
"---\n",
"[A] https://lifelines.readthedocs.io/en/latest/jupyter_notebooks/Proportional%20hazard%20assumption.html\n",
"[B] https://lifelines.readthedocs.io/en/latest/jupyter_notebooks/Proportional%20hazard%20assumption.html#Bin-variable-and-stratify-on-it\n",
"[C] https://lifelines.readthedocs.io/en/latest/jupyter_notebooks/Proportional%20hazard%20assumption.html#Introduce-time-varying-covariates\n",
"[D] https://lifelines.readthedocs.io/en/latest/jupyter_notebooks/Proportional%20hazard%20assumption.html#Modify-the-functional-form\n",
"[E] https://lifelines.readthedocs.io/en/latest/jupyter_notebooks/Proportional%20hazard%20assumption.html#Stratification\n",
"\n"
]
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",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"image/png": {
"height": 284,
"width": 424
},
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"image/png": {
"height": 284,
"width": 424
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"cph.check_assumptions(rossi, p_value_threshold=0.05, show_plots=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alternatively, you can use the proportional hazard test outside of `check_assumptions`:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <tbody>\n",
" <tr>\n",
" <th>time_transform</th>\n",
" <td>rank</td>\n",
" </tr>\n",
" <tr>\n",
" <th>null_distribution</th>\n",
" <td>chi squared</td>\n",
" </tr>\n",
" <tr>\n",
" <th>degrees_of_freedom</th>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>model</th>\n",
" <td>untransformed variables</td>\n",
" </tr>\n",
" <tr>\n",
" <th>test_name</th>\n",
" <td>proportional_hazard_test</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div><table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>test_statistic</th>\n",
" <th>p</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>age</th>\n",
" <td>11.453</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fin</th>\n",
" <td>0.015</td>\n",
" <td>0.902</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mar</th>\n",
" <td>0.709</td>\n",
" <td>0.400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>paro</th>\n",
" <td>0.134</td>\n",
" <td>0.714</td>\n",
" </tr>\n",
" <tr>\n",
" <th>prio</th>\n",
" <td>0.019</td>\n",
" <td>0.891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>race</th>\n",
" <td>1.426</td>\n",
" <td>0.232</td>\n",
" </tr>\n",
" <tr>\n",
" <th>wexp</th>\n",
" <td>7.315</td>\n",
" <td>0.007</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from lifelines.statistics import proportional_hazard_test\n",
"\n",
"results = proportional_hazard_test(cph, rossi, time_transform='rank')\n",
"results.print_summary(decimals=3, model=\"untransformed variables\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Stratification\n",
"\n",
"\n",
"In the advice above, we can see that `wexp` has small cardinality, so we can easily fix that by specifying it in the `strata`. What does the `strata` do? Let's go back to the proportional hazard assumption.\n",
"\n",
"In the introduction, we said that the proportional hazard assumption was that \n",
"\n",
"$$ h_i(t) = a_i h(t)$$\n",
"\n",
"In a simple case, it may be that there are two subgroups that have _very_ different baseline hazards. That is, we can split the dataset into subsamples based on some variable (we call this the stratifying variable), run the Cox model on all subsamples, and compare their baseline hazards. If these baseline hazards are _very_ different, then clearly the formula above is wrong - the $h(t)$ is some weighted average of the subgroups' baseline hazards. This ill fitting average baseline can cause $a_i$ to have time-dependent influence. A better model might be:\n",
"\n",
"$$ h_{i |i\\in G}(t) = a_i h_G(t)$$\n",
"\n",
"where now we have a unique baseline hazard _per_ subgroup $G$. Because of the way the Cox model is designed, inference of the coefficients is identical (expect now there are more baseline hazards, and no variation of the stratifying variable within a subgroup $G$). \n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <tbody>\n",
" <tr>\n",
" <th>model</th>\n",
" <td>lifelines.CoxPHFitter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>duration col</th>\n",
" <td>'week'</td>\n",
" </tr>\n",
" <tr>\n",
" <th>event col</th>\n",
" <td>'arrest'</td>\n",
" </tr>\n",
" <tr>\n",
" <th>strata</th>\n",
" <td>[wexp]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>baseline estimation</th>\n",
" <td>breslow</td>\n",
" </tr>\n",
" <tr>\n",
" <th>number of observations</th>\n",
" <td>432</td>\n",
" </tr>\n",
" <tr>\n",
" <th>number of events observed</th>\n",
" <td>114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>partial log-likelihood</th>\n",
" <td>-580.89</td>\n",
" </tr>\n",
" <tr>\n",
" <th>time fit was run</th>\n",
" <td>2020-07-26 22:15:41 UTC</td>\n",
" </tr>\n",
" <tr>\n",
" <th>model</th>\n",
" <td>wexp in strata</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div><table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>coef</th>\n",
" <th>exp(coef)</th>\n",
" <th>se(coef)</th>\n",
" <th>coef lower 95%</th>\n",
" <th>coef upper 95%</th>\n",
" <th>exp(coef) lower 95%</th>\n",
" <th>exp(coef) upper 95%</th>\n",
" <th>z</th>\n",
" <th>p</th>\n",
" <th>-log2(p)</th>\n",
" </tr>\n",
" <tr>\n",
" <th>covariate</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>fin</th>\n",
" <td>-0.38</td>\n",
" <td>0.68</td>\n",
" <td>0.19</td>\n",
" <td>-0.76</td>\n",
" <td>-0.01</td>\n",
" <td>0.47</td>\n",
" <td>0.99</td>\n",
" <td>-1.99</td>\n",
" <td>0.05</td>\n",
" <td>4.42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>age</th>\n",
" <td>-0.06</td>\n",
" <td>0.94</td>\n",
" <td>0.02</td>\n",
" <td>-0.10</td>\n",
" <td>-0.01</td>\n",
" <td>0.90</td>\n",
" <td>0.99</td>\n",
" <td>-2.64</td>\n",
" <td>0.01</td>\n",
" <td>6.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>race</th>\n",
" <td>0.31</td>\n",
" <td>1.36</td>\n",
" <td>0.31</td>\n",
" <td>-0.30</td>\n",
" <td>0.91</td>\n",
" <td>0.74</td>\n",
" <td>2.49</td>\n",
" <td>1.00</td>\n",
" <td>0.32</td>\n",
" <td>1.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mar</th>\n",
" <td>-0.45</td>\n",
" <td>0.64</td>\n",
" <td>0.38</td>\n",
" <td>-1.20</td>\n",
" <td>0.29</td>\n",
" <td>0.30</td>\n",
" <td>1.34</td>\n",
" <td>-1.19</td>\n",
" <td>0.23</td>\n",
" <td>2.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>paro</th>\n",
" <td>-0.08</td>\n",
" <td>0.92</td>\n",
" <td>0.20</td>\n",
" <td>-0.47</td>\n",
" <td>0.30</td>\n",
" <td>0.63</td>\n",
" <td>1.35</td>\n",
" <td>-0.42</td>\n",
" <td>0.67</td>\n",
" <td>0.57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>prio</th>\n",
" <td>0.09</td>\n",
" <td>1.09</td>\n",
" <td>0.03</td>\n",
" <td>0.03</td>\n",
" <td>0.15</td>\n",
" <td>1.04</td>\n",
" <td>1.16</td>\n",
" <td>3.16</td>\n",
" <td><0.005</td>\n",
" <td>9.33</td>\n",
" </tr>\n",
" </tbody>\n",
"</table><div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <tbody>\n",
" <tr>\n",
" <th>Concordance</th>\n",
" <td>0.61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Partial AIC</th>\n",
" <td>1173.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>log-likelihood ratio test</th>\n",
" <td>23.77 on 6 df</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-log2(p) of ll-ratio test</th>\n",
" <td>10.77</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/latex": [
"\\begin{tabular}{lrrrrrrrrrr}\n",
"\\toprule\n",
"{} & coef & exp(coef) & se(coef) & coef lower 95\\% & coef upper 95\\% & exp(coef) lower 95\\% & exp(coef) upper 95\\% & z & p & -log2(p) \\\\\n",
"covariate & & & & & & & & & & \\\\\n",
"\\midrule\n",
"fin & -0.38 & 0.68 & 0.19 & -0.76 & -0.01 & 0.47 & 0.99 & -1.99 & 0.05 & 4.42 \\\\\n",
"age & -0.06 & 0.94 & 0.02 & -0.10 & -0.01 & 0.90 & 0.99 & -2.64 & 0.01 & 6.91 \\\\\n",
"race & 0.31 & 1.36 & 0.31 & -0.30 & 0.91 & 0.74 & 2.49 & 1.00 & 0.32 & 1.65 \\\\\n",
"mar & -0.45 & 0.64 & 0.38 & -1.20 & 0.29 & 0.30 & 1.34 & -1.19 & 0.23 & 2.09 \\\\\n",
"paro & -0.08 & 0.92 & 0.20 & -0.47 & 0.30 & 0.63 & 1.35 & -0.42 & 0.67 & 0.57 \\\\\n",
"prio & 0.09 & 1.09 & 0.03 & 0.03 & 0.15 & 1.04 & 1.16 & 3.16 & 0.00 & 9.33 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n"
],
"text/plain": [
"<lifelines.CoxPHFitter: fitted with 432 total observations, 318 right-censored observations>\n",
" duration col = 'week'\n",
" event col = 'arrest'\n",
" strata = ['wexp']\n",
" baseline estimation = breslow\n",
" number of observations = 432\n",
"number of events observed = 114\n",
" partial log-likelihood = -580.89\n",
" time fit was run = 2020-07-26 22:15:41 UTC\n",
" model = wexp in strata\n",
"\n",
"---\n",
" coef exp(coef) se(coef) coef lower 95% coef upper 95% exp(coef) lower 95% exp(coef) upper 95%\n",
"covariate \n",
"fin -0.38 0.68 0.19 -0.76 -0.01 0.47 0.99\n",
"age -0.06 0.94 0.02 -0.10 -0.01 0.90 0.99\n",
"race 0.31 1.36 0.31 -0.30 0.91 0.74 2.49\n",
"mar -0.45 0.64 0.38 -1.20 0.29 0.30 1.34\n",
"paro -0.08 0.92 0.20 -0.47 0.30 0.63 1.35\n",
"prio 0.09 1.09 0.03 0.03 0.15 1.04 1.16\n",
" z p -log2(p)\n",
"covariate \n",
"fin -1.99 0.05 4.42\n",
"age -2.64 0.01 6.91\n",
"race 1.00 0.32 1.65\n",
"mar -1.19 0.23 2.09\n",
"paro -0.42 0.67 0.57\n",
"prio 3.16 <0.005 9.33\n",
"---\n",
"Concordance = 0.61\n",
"Partial AIC = 1173.77\n",
"log-likelihood ratio test = 23.77 on 6 df\n",
"-log2(p) of ll-ratio test = 10.77"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cph.fit(rossi, 'week', 'arrest', strata=['wexp'])\n",
"cph.print_summary(model=\"wexp in strata\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",