OpenEpi

Key takeaways

OpenEpi belongs to mathematics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect OpenEpi to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of OpenEpi from memory before moving on to harder problems.

Reference excerpt

OpenEpi is a free, web-based, open source, operating system-independent series of programs for use in epidemiology, biostatistics, public health, and medicine, providing a number of epidemiologic and statistical tools for summary data. OpenEpi was developed in JavaScript and HTML, and can be run in modern web browsers. The program can be run from the OpenEpi website or downloaded and run without a web connection. The source code and documentation is downloadable and freely available for use by other investigators. OpenEpi has been reviewed, both by media organizations and in research journals. The OpenEpi developers have had extensive experience in the development and testing of Epi Info, a program developed by the Centers for Disease Control and Prevention (CDC) and widely used around the world for data entry and analysis. OpenEpi was developed to perform analyses found in the DOS version of Epi Info modules StatCalc and EpiTable, to improve upon the types of analyses provided by these modules, and to provide a number of tools and calculations not currently available in Epi Info. It is the first step toward an entirely web-based set of epidemiologic software tools. OpenEpi can be thought of as an important companion to Epi Info and to other programs such as SAS, PSPP, SPSS, Stata, SYSTAT, Minitab, Epidata, and R (see the R programming language). Another functionally similar Windows-based program is Winpepi. See also list of statistical packages and comparison of statistical packages. Both OpenEpi and Epi Info were developed with the goal of providing tools for low and moderate resource areas of the world. The initial development of OpenEpi was supported by a grant from the Bill and Melinda Gates Foundation to Emory University.

Types The types of calculations currently performed by OpenEpi include:

Various confidence intervals for proportions, rates, standardized mortality ratio, mean, median, percentiles 2x2 crude and stratified tables for count and rate data Matched case-control analysis Test for trend with count data Independent t-test and one-way ANOVA Diagnostic and screening test analyses with receiver operating characteristic (ROC) curves Sample size for proportions, cross-sectional surveys, unmatched case-control, cohort, randomized controlled trials, and comparison of two means Power calculations for proportions (unmatched case-control, cross-sectional, cohort, randomized controlled trials) and for the comparison of two means Random number generator For epidemiologists and other health researchers, OpenEpi performs a number of calculations based on tables not found in most epidemiologic and statistical packages. For example, for a single 2x2 table, in addition to the results presented in other programs, OpenEpi provides estimates for:

Etiologic or prevented fraction in the population and in exposed with confidence intervals, based on risk, odds, or rate data The cross-product and MLE odds ratio estimate Mid-p exact p-values and confidence limits for the odds ratio Calculations of rate ratios and rate differences with confidence intervals and statistical tests. For stratified 2x2 tables with count data, OpenEpi provides:

Mantel-Haenszel (MH) and precision-based estimates of the risk ratio and odds ratio Precision-based adjusted risk difference Tests for interaction for the risk ratio, odds ratio, and risk difference Four different confidence limit methods for the odds ratio. Similar to Epi Info, in a stratified analysis, both crude and adjusted estimates are provided so that the assessment of confounding can be made. With rate data, OpenEpi provides adjusted rate ratio's and rate differences, and tests for interaction. Finally, with count data, OpenEpi also performs a test for trend, for both crude data and stratified data. In addition to being used to analyze data by health researchers, OpenEpi has been used as a training tool for teaching epidemiology to students at: Emory University, University of Massachusetts, University of Michigan, University of Minnesota, Morehouse College, Columbia University, University of Wisconsin, San Jose State University, University of Medicine and Dentistry of New Jersey, University of Washington, and elsewhere. This includes campus-based and distance learning courses. Because OpenEpi is easy to use, requires no programming experience, and can be run on the internet, students can use the program and focus on the interpretation of results. Users can run the program in English, French, Spanish, Portuguese or Italian. Comments and suggestions for improvements are welcomed and the developers respond to user queries. The developers encourage others to develop modules that could be added to OpenEpi and provide a developer's tool at the website. Planned future development include improvements to existing modules, development of new modules, translation into other languages, and add the ability to cut and paste data and/or read data files.

Illustrations

Worked examples

Example 1 — a first encounter with OpenEpi

Start with the simplest possible case. Write down what OpenEpi claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to OpenEpi before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about OpenEpi ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of OpenEpi

In research: OpenEpi appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses OpenEpi in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: OpenEpi is common in secondary-school and first-year university syllabi. It links to neighbouring topics Biostatistics, Epidemiology, Free statistical software, so understanding it makes those chapters shorter.
In everyday life: Look for OpenEpi outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

How to study OpenEpi in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what OpenEpi means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain OpenEpi out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is OpenEpi in simple terms?

OpenEpi is a free, web-based, open source, operating system-independent series of programs for use in epidemiology, biostatistics, public health, and medicine, providing a number of epidemiologic and statistical tools for summary data. OpenEpi was developed in JavaScript and HTML, and can be run in…

Why does OpenEpi matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study OpenEpi?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on OpenEpi.