zEpid

zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in python3. The purpose of this package is to provide a toolset to make epidemiology e-z. A variety of calculations and plots can be generated through various functions. For a sample walkthrough of what this package is capable of, please look to the introduction to Python 3 for epidemiologists at https://github.com/pzivich/Python-for-Epidemiologists

A few highlights: basic epidemiology calculations, easily create functional form assessment plots, easily create effect measure plots, generate and conduct diagnostic tests on inverse probability weight, augmented inverse probability weight estimator, time-varying g-computation algorithm

If you have any requests for items to be included, please contact me and I will work on adding any requested features. You can contact me either through github (https://github.com/pzivich), email (gmail: zepidpy), or twitter (@zepidpy).

Installation

Installing:

You can install zEpid using pip install zepid

Dependencies:

pandas >= 0.18.0, numpy, statsmodels >= 0.7.0, matplotlib >= 2.0, scipy, tabulate

Module Features

Measures

Calculate measures directly from a pandas dataframe object. Implemented measures include; risk ratio, risk difference, odds ratio, incidence rate ratio, incidence rate difference, number needed to treat, sensitivity, specificity, population attributable fraction, attributable community risk, standardized mean difference

Other handy features include; splines, Table 1 generator, interaction contrast, interaction contrast ratio

http://zepid.readthedocs.io/en/latest/Measures.html

Calculator

Calculate measures from summary data. Functions that calculate summary measures from the pandas dataframe use these functions in the background. Implemented measures include; risk ratio, risk difference, odds ratio, incidence rate ratio, incidence rate difference, number needed to treat, sensitivity, specificity, positive predictive value, negative predictive value, screening cost analyzer, counternull p-values, convert odds to proportions, convert proportions to odds, population attributable fraction, attributable community risk, standardized mean difference

http://zepid.readthedocs.io/en/latest/Calculator.html

Graphics

Uses matplotlib in the background to generate some useful plots. Implemented plots include; functional form assessment (with statsmodels output), p-value plots/functions, spaghetti plot, effect measure plot (forest plot), receiver-operator curve, dynamic risk plot

http://zepid.readthedocs.io/en/latest/Graphics.html

Causal

Causal is a new branch that houses all the causal inference methods implemented.

http://zepid.readthedocs.io/en/latest/Causal.html

G-Computation Algorithm

Current implementation includes; time-fixed exposure g-formula and time-varying g-formula

Inverse Probability Weights

Current implementation includes; IP Treatment W, IP Censoring W, IP Missing W. Diagnostics are also available for IPTW

Augmented Inverse Probability Weights

Current implementation includes the estimator described by Funk et al 2011 AJE

Targeted Maximum Likelihood Estimator

Current implementation is a simple TMLE. At the current state, it does NOT include any algorithms in the background for variable selection or machine learning algorithms (these are to be added in the future)

Sensitivity Analyses

Includes trapezoidal distribution generator, corrected Risk Ratio

http://zepid.readthedocs.io/en/latest/Sensitivity%20Analyses.html