Process of validating a survey
They are now harnessing the power of food to reverse disease and promote health. The idea was to have the bottom level being the SAD, with LESS than 10% of calories from whole plants.
And those physicians are discovering that our powerful 4Leaf Survey is quickly becoming the most important tool in their bag. John Green in Australia says that he uses it ten times a day and that he could no longer live without it. The next level is “Better than Most” — with 10 to 20% from whole plants.
In New York City, Arizona, Australia, North Carolina, Florida, California, Canada, Ireland and in the Finger Lakes Region of New York state, that process is well underway. I started out wanting to develop a simple survey that would assess a person’s diet compared to Dr. Colin Campbell’s definition of an optimal diet: In 2009, I reviewed the concept of six levels of eating with Colin at his breakfast table in Ithaca.
Many primary care physicians who are fed up with “disease management,” are embracing a whole new way of practicing medicine. He loved it because it was positive and emphasized the maximization of the best food—not just the avoidance of meat, dairy, etc.
”, “Do people in these groups communicate with you in a timely way about [focal work process]?
”, “Do people in these groups communicate with you accurately about [focal work process]?
The key to making use of this potentially invalid data is data validation.
Data visualization provides an entirely new way to determine if your data is valid.
Construct validity refers to the extent to which operationalizations of a construct (i.e., practical surveys developed from a theory) do actually measure what the theory says they do.
However, to truly see whether data has been validated, a better way of viewing the potential problems with the dataset is needed.
The most common flaw in a data set is missing data, typically in the form of partial records.
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