This is a short tutorial for users that want to get into the thick of things right away. Evil dungeon mac os. However, we highly recommend that users read the other docs provided in order to get a feel for all of the functionality provided in Ananke. The estimators here are based on theory in our paper Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables (Bhattacharya, Nabi, & Shpitser, 2020).
Following are the necessary packages that need to be imported for this tutorial.
Creating a Causal Graph¶
In Ananke, the most frequently used causal graph is an acyclic directed mixed graph (ADMG). Roughly, directed edges (X rightarrow Y) indicate (X) is a direct cause of (Y) and bidirected edges (X leftrightarrow Y) indicate the presence of one or more unmeasured confounders between (X) and (Y.) Let's say we are studying the efficacy of a new antiretroviral therapy vs. an old one. Gullys vengeance mac os. Call this the treatment (T) where (T=1) represents receiving thenew drug and (T=0) represents receiving the old. Our outcome of interest is the patients CD4 counts post treatment. Thus, our target of interest (in potential outcomes notation) is the counterfactual contrast (psi equiv E[Y(1)] - E[Y(0)].) This is how one may create a causal graph, with additional variables relevant to the given problem.
Identification of the Causal Effect¶
Using Ananke, we can ask whether the effect of a given treatment (T) on a given outcome (Y) is identified or not. We have implemented the one line ID algorithm provided in Nested Markov Properties for Acyclic Directed Mixed Graphs which is sound and complete in identifying (p(Y(t))) or equivalently (p(Y | do(t))). We show how to use this in Ananke through the following example.
Estimation of the Causal Effect¶
Mac OS X: OS: OSX 10.8 or later Processor: 1.7GHz Dual Core (4th generation i5 or equivalent) or better Memory: 4 GB RAM Graphics: OpenGL SM 2.0 with 512MB of VRAM or better Storage: 4 GB available space. Linux: OS: Ubuntu 12.04 or later Processor: 1.7GHz Dual Core (4th generation i5 or equivalent) or better Memory: 4 GB RAM. In 1984, Apple debuted the operating system that is now known as the 'Classic' Mac OS with its release of the original Macintosh System Software. The system, rebranded 'Mac OS' in 1996, was preinstalled on every Macintosh until 2002 and offered on Macintosh clones for a short time in the 1990s. Mac OS's from the original 1.0 until OS X. I started & ran a business on Turbo Pascal starting in 1987, on an XT clone.
- In 1984, Apple debuted the operating system that is now known as the 'Classic' Mac OS with its release of the original Macintosh System Software. The system, rebranded 'Mac OS' in 1996, was preinstalled on every Macintosh until 2002 and offered on Macintosh clones for a short time in the 1990s.
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Ananke provides an easy interface in order to compute causal effects. First, we instantiate a CausalEffect object.
In this case, it recommends Efficient Generalized AIPW which is to say, that the estimator used to compute the effect in this case looks a lot like Augmented IPW (which is doubly robust). Further, Ananke uses semiparametric theory in order to provide an estimator that achieves the lowest asymptotic variance.
Given the list of estimators, it is up to the user to specify what estimators they want to work with. For instance, if the user decides to use the efficient generalized AIPW, they only need to use the keyword given in front of it, i.e., eff-aipw, when computing the effect. All the nuisance models are fit using generalized linear models provided in the statsmodels. Users interested in using different modeling approaches can refer to the documentation on accessing the functional form ofthe influence functions at the end of this notebook.
Let's load up some toy data and use all of the available estimators in order to compute the causal effect.
In addition, the user can run bootstraps and obtain ((1-alpha)*100%) confidence level for the causal effect point estimate. The user needs to specify two arguments: number of bootstraps n_bootstraps and the significance level (alpha)alpha. The confidence interval can then be obtained via bootstrap percentile intervals, as described in All of Nonparametric Statistics. In this case, the call to thecompute_effect returns three values: the first corresponds to the effect computed on the original data, the second and third are the pre-specified lower and upper quantiles, i.e., ((frac{alpha}{2}, 1 - frac{alpha}{2}).) The default value for (alpha) is set to be (0.05). We illustrate this through the following toy example.
While Ananke has its own built-in esimation strategy for every identifiable causal effect concerning a single treatment and outcome, users may be interested in building their own estimators based on the identifying functionals/nonparametric influence functions. This allows users to use their own preferred estimation strategies such as sample splitting, using their preferred machine learning model etc. Below, we provide an example for a new causal graph reflecting some background knowledge and weare interested in the causal effect of the treatment (T) on the outcome (Y.)
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As I'm taking notes or writing in Org-mode, I often want to insert screenshots inline with the text. While Org supports inserting and displaying inline images, the assumption is that the image is already somewhere in the file system and we just want to link to it.
The org-download package eases the task of downloading or copying images and attaching them to a document, and it even has an org-download-screenshot command, but this assumes you want to initiate the screenshot from within Emacs, whereas the workflow I prefer is like this:
- Capture screenshot using the macOS built-in screenshot tool (Shift-⌘-5) and leave it in the clipboard.
- Paste the image into the document I'm working on.
Fortunately, org-download allows customizing the command used by the org-download-screenshot command. Together with the pngpaste utility, this can be used to make org-download-screenshot store the image from the clipboard to disk, and insert it into the document. This is my configuration:
With this configuration, images are stored in a directory named images under the current directory, in a flat directory structure and each file is prepended with a timestamp (I would prefer not to use timestamps, but org-download uses a fixed filename for screenshots, which makes it difficult to insert multiple screenshots in the same document). You may want to check the org-download documentation and configure these settings to your liking.
Finally, I bind org-download-screenshot to Ctrl-⌘-y to keep it similar to the default Ctrl-y for pasting the clipboard and to easily perform step 2 of the workflow described above.
Mac Os Download
Now when I want to insert a screenshot in a document, I simply press Shift-⌘-5, capture the screenshot, switch back to Emacs, press Ctrl-⌘-y, and done. It looks like this:
And without inline image display, we can see that the screenshot is automatically stored inside the images/ directory:
Thanks to this thread at Stack Overflow for the base ideas and pointers for this configuration.
Note: The same technique could be used in non-macOS systems by invoking a corresponding utility that does the same. From the thread above you can get examples for both Windows and Linux.
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