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Validating technique in psycohology

In this way, cross-validation mimics the advantages of an independent replication with the same amount of collected data (Yarkoni and Westfall, 2017). doi: 10.1037/a0015108 Cross Ref Full Text | Google Scholar Schrouff, J., Rosa, M. Splitting data into training and test subsets can be done using various methods, including holdout cross-validation, k-fold cross-validation, leave-one-subject-out cross-validation, and leave-one-trial-out cross-validation.

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As an extreme example, if the number of parameters of a model is the same as or greater than the number of observations, then a model can perfectly predict the training data simply by memorizing the data in its entirety.

Direct replications are replication attempts that aim at reproducing the exact effects as obtained by a previous study, incorporating the exact experimental conditions.

In contrast, conceptual replications examine the general nature of the previously obtained effects, while aiming at extending the original effects to a new context.

The validity and generalizability of the generated model is then tested on the k observation (test dataset). Bayesian tests to quantify the result of a replication attempt.

Cross-validation has the computational advantage that it avoids fitting a model too closely to the peculiarities of a data set (overfitting). doi: 10.2139/ssrn.2259879 Pub Med Abstract | Cross Ref Full Text | Google Scholar Varoquaux, G., Raamana, P. A., Hoyos-Idrobo, A., Schwartz, Y., and Thirion, B. Assessing and tuning brain decoders: cross-validation, caveats, and guidelines. doi: 10.1016/j.neuroimage.20 Pub Med Abstract | Cross Ref Full Text | Google Scholar Verhagen, J., and Wagenmakers, E.


  1. Using Validation techniques we offer disoriented elderly an opportunity to express what they wish. Theory from Humanistic psychology Maslow, Rogers, etc.

  2. Cognitive mapping techniques refer to methods used to elicit the structure and. developments in the cognitive psychology of the categorization of concepts.

  3. Cross-validation entails a set of techniques that partition the dataset and repeatedly.

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