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Is a longitudinal study really by definition/always correlational?

  1. How about a repeated-measures experiment: I would've called that an experimental longitudinal design. (For example, you randomly assign subjects to 1 of 2 groups; you collect data 1x before a manipulation, 1x right afterwards, then again 1x in a 3-year-follow-up.) ... or is that a contradiction in terms?!

  2. How about this even more specific scenario:
    week 1: Group A gets a drug, Group B a placebo
    week 2: neither group gets anything
    week 3: Group A gets the placebo, Group B the drug
    data collection at the end of each week.
    Now, does it matter how you analyze this/ which research question you ask in order to "define" the design? e.g., if you just use a t-test of week 3 data, you've obviously neglected all longitudinal aspects and would call it an experiment... but would it work the other way around, so when you are mainly interested in the repeated measures-aspect, that you could call this longitudinal, but still enter all data into your analysis (e.g., an ANOVA, or even better, a regression analysis?

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    $\begingroup$ What do you mean by "is a longitudinal study always correlational?" Are you asking whether the measurements are always correlated, or whether you are limited to correlational analyses of the data? $\endgroup$ – Bosley Feb 18 '15 at 3:17
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Is a longitudinal study really by definition/always correlational?

The short answer is, no.

The long answer is, well, both "longitudinal" and "correlational" are tricky words.

In the case of "longitudinal", all the word requires is that measurements are repeated over time. Any repeated-measures experiment satisfies this criterion. But in practice, the word "longitudinal" usually refers to measurements repeated over a relatively long timespan, and to study designs that aren't true experiments (that is, that don't randomly assign subjects to values of the independent variables).

As for "correlational", all the word requires is a data analysis presented in terms of correlation coefficients. But because of a trend for correlation to be used when analyzing data from non-experimental studies, psychologists (at least) have gotten in the habit of using the term "correlational" to mean "non-experimental", hence terms like "correlational design" even when correlation plays no role in the design of the study, only in the data analysis.

So, most studies called longitudinal studies would also be called correlational, but there are also studies one could justifiably call longitudinal (like your two examples) that are correlational neither in the sense of being non-experimental nor in the sense of using correlation coefficients in the data analysis.

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