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Is it (always) better to build a model prior to viewing the data?

I actually consider building an initial model to be part of the process of validating the data (it doesn't have to be all that good, but does need to be credible), but given how rarely one gets a ...
John L. Ries's user avatar
12 votes

Is it (always) better to build a model prior to viewing the data?

There is a division, or gradation, between exploratory and confirmatory statistics. Both have value. Mixing the two is dangerous. At one end, we have a lot of data mining. Some of this comes very ...
Peter Flom's user avatar
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16 votes
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Is it (always) better to build a model prior to viewing the data?

If you build a model before seeing the data you are more likely to get results (effect sizes, p-values, etc.) that correctly relate the variables in the model to the process you are studying. That is, ...
dariober's user avatar
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17 votes

Is it (always) better to build a model prior to viewing the data?

The problem is that of potential bias in p-values and confidence intervals as well as overfitting or poor predictive performance without making adjustments for the process of choosing the model. ...
Rick Hass's user avatar
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2 votes
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Would withholding marks until students respond to a survey bias the responses?

Satisficing is at least one problem to consider. For instance, people may simply rush through the survey as an answering strategy, in particular if the survey is long. Non-response bias may be ...
J-J-J's user avatar
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