DAGitty - drawing and analyzing causal diagrams DAGs

Launch DAGitty online in your browser. Learn more about DAGs and DAGitty. Join the mailing list. Or contact the author directly. Download DAGittys source for offline use. DAGitty is a browser-based environment for creating, editing, and analyzing causal models also known as directed acyclic graphs or causal Bayesian networks. The focus is on the use of causal diagrams for minimizing bias in empirical studies in epidemiology and other disciplines. For background information, see the learn. Because th.

OVERVIEW

This website dagitty.net presently has a traffic ranking of zero (the lower the higher page views). We have evaluated ten pages inside the web site dagitty.net and found fourteen websites interfacing with dagitty.net. We were able to acquire two contacts and locations for dagitty.net to help you reach them. We were able to acquire one public web platforms linked to dagitty.net. This website dagitty.net has been online for seven hundred and twenty-four weeks, seventeen days, fourteen hours, and eighteen minutes.
Pages Analyzed
10
Links to this site
14
Contacts
2
Locations
2
Social Links
1
Online Since
Nov 2010

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DAGITTY.NET HISTORY

This website dagitty.net was first documented on November 23, 2010. It was last updated on the date of November 17, 2013. This site will go back on the market on the date of November 23, 2014. It is currently seven hundred and twenty-four weeks, seventeen days, fourteen hours, and eighteen minutes old.
REGISTERED
November
2010
UPDATED
November
2013
EXPIRED
November
2014

COMPANY PERIOD OF EXISTANCE

13
YEARS
10
MONTHS
17
DAYS

LINKS TO BUSINESS

DIfE -- Deutsches Institut für Ernährungsforschung -- Abteilung Epidemiologie

Willkommen auf der Plattform für Online-Instrumente der Abteilung Epidemiologie. Online-Plattform für Datenerhebungsinstrumente und Verwaltung von epidemiologischen Studien. Online Version des Deutschen Diabetes Risiko Test. Das Ziel der Abteilung .

Diogo Ferrari Life is the art of drawing sufficient conclusions from insufficient data.

Life is the art of drawing sufficient conclusions from insufficient data. In general, I prefer to use the plot functions that comes in the basic packages in R to plot and display data. However, ggplot and lattice can be very handy for some tasks. I was visiting randomly some webpages on the internet this days and I came accross this blog. This entry was posted in R.

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CONTACTS

zeile2 GbR

Benjamin Feldner

Fuenfhausen 1

Luebeck, 23552

DE

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Oskar-Messter-Str. 33

Ismaning, 85737

DE

DAGITTY.NET HOST

I revealed that a lone page on dagitty.net took five hundred and ninety-four milliseconds to come up. We could not discover a SSL certificate, so our web crawlers consider dagitty.net not secure.
Load time
0.594 seconds
SSL
NOT SECURE
Internet Address
78.46.52.22

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ns.namespace4you.com
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SERVER OPERATING SYSTEM AND ENCODING

I diagnosed that dagitty.net is operating the Apache/2.2.22 (Debian) operating system.

TITLE

DAGitty - drawing and analyzing causal diagrams DAGs

DESCRIPTION

Launch DAGitty online in your browser. Learn more about DAGs and DAGitty. Join the mailing list. Or contact the author directly. Download DAGittys source for offline use. DAGitty is a browser-based environment for creating, editing, and analyzing causal models also known as directed acyclic graphs or causal Bayesian networks. The focus is on the use of causal diagrams for minimizing bias in empirical studies in epidemiology and other disciplines. For background information, see the learn. Because th.

CONTENT

This website had the following on the web page, "Launch DAGitty online in your browser." Our analyzers viewed that the web site said " Learn more about DAGs and DAGitty." The Website also said " Or contact the author directly. Download DAGittys source for offline use. DAGitty is a browser-based environment for creating, editing, and analyzing causal models also known as directed acyclic graphs or causal Bayesian networks. The focus is on the use of causal diagrams for minimizing bias in empirical studies in epidemiology and other disciplines. For background information, see the learn."

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