Examples of using Digital experiments in English and their translations into Indonesian
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Colloquial
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Ecclesiastic
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Ecclesiastic
By this point,I hope that you are excited about the possibilities of doing your own digital experiments.
In conclusion, digital experiments can have dramatically different cost structures than analog experiments. .
By this point,I hope that you are excited about the possibilities of doing your own digital experiments.
In between these two extremes, there are partially digital experiments that use a combination of analog and digital systems.
But if you don't work at a tech company,you might think that you can't run digital experiments.
In between these two extremes there are partially digital experiments that use a combination of analog and digital systems for the four steps.
This point is so important,I will return to it towards the end of the chapter when I offer advice about creating digital experiments.
Even though digital experiments have low variable costs, you can create a lot of exciting opportunities when you drive the variable cost all the way to zero.
Thus, I expect that construct validitywill tend to be a bigger concern in digital experiments than in analog experiments. .
In digital experiments, however, these data constraints are less common because researchers tend to have more participants and know more about them.
But, if you don't work at a techcompany you might think that you can't run digital experiments. Fortunately, that's wrong;
Digital experiments can have dramatically different cost structures, and this enables researchers to run experiments that were impossible in the past.
This background information, which is called pre-treatment information,is often available in digital experiments because they take place in fully measured environments.
Then, in section 4.3, I will describe the difference between lab experiments and field experiments andthe differences between analog experiments and digital experiments.
In general, analog experiments have low fixed costs andhigh variable costs, while digital experiments have high fixed costs and low variable costs(figure 4.19).
Logistically, the easiest way to do digital experiments is to overlay your experiment on top of an existing environment, enabling you to run a digital field experiment. .
In general, analog experiments have low fixed costs andhigh variable costs, and digital experiments have high fixed costs and low variable costs(Figure 4.18).
But in digital experiments, particularly those with zero variable cost, researchers don't face a cost constraint on the size of their experiment, and this has the potential to lead to unnecessarily large experiments. .
This background information, which is called pre-treatment information,is often available in digital experiments because they are run on top of always-on measurement systems(see chapter 2).
In digital experiments where researchers partner with companies or governments to deliver treatments and use always-on data systems to measure outcomes, the match between the experiment and the theoretical constructs may be less tight.
When researchers already have pre-treatment information,as is the case in many digital experiments, mixed designs are generally preferable to between-subjects designs because they result in improved precision of estimates.
In digital experiments where researchers partner with companies or governments to deliver treatments and use always-on data systems to measure outcomes, the match between the experiment and the theoretical constructs may be less tight.
When researchers already have pre-treatment information,as is the case in many digital experiments, mixed designs are generally preferable to between-subjects designs because they result in improved precision of estimates.
In digital experiments where researchers partner with companies or governments to deliver treatments and use always-on data systems to measure outcomes, the match between the experiment and the theoretical constructs may be less tight.
Not only can researchers run massive experiments, they can also take advantage of the specific nature of digital experiments to improve validity, estimate heterogeneity of treatment effects, and isolate mechanisms.
What has changed, however, is that the data environment in digital experiments has created new opportunities such as using machine learning methods to estimate heterogeneity of treatment effects(Imai and Ratkovic 2013).
It is tricky to offer a formal definition of this dimension,but a useful working definition is that fully digital experiments are experiments that make use of digital infrastructure to recruit participants, randomize, deliver treatments, and measure outcomes.
It seems like we have entered a post-responsive era, followed by digital experiments, moving backgrounds, innovative interactions, unique typography, hero illustrations, and socially conscious design fueled by equality, inclusivity, and accessibility.
It is tricky to offer a formal definition of this dimension,but a useful working definition is that fully digital experiments are experiments that make use of digital infrastructure to recruit participants, randomize, deliver treatments, and measure outcomes.
Finally, to foreshadow an idea that will come later whenI offer advice about designing digital experiments, a_mixed design_combines the improved precision of within-subjects designs and the protection against confounding of between-subjects designs(figure 4.5).