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Example of direct replication and conceptual replication. There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [3]
An investigation of replication rates in psychology in 2012 indicated higher success rates of replication in replication studies when there was author overlap with the original authors of a study [221] (91.7% successful replication rates in studies with author overlap compared to 64.6% successful replication rates without author overlap).
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
The Reproducibility Project is a series of crowdsourced collaborations aiming to reproduce published scientific studies, finding high rates of results which could not be replicated. It has resulted in two major initiatives focusing on the fields of psychology [ 1 ] and cancer biology. [ 2 ]
A replication attempt with a sample from a more diverse population, over 10 times larger than the original study, showed only half the effect of the original study. The replication suggested that economic background, rather than willpower, explained the other half. [6] [7] The predictive power of the marshmallow test was challenged in a 2020 study.
In Economics, a replication of 18 experimental studies in two major journals, found a failure rate comparable to psychology or medicine (39%). [39] Several global surveys have reported a growing uneasiness of scientific communities over reproducibility and other issues of research transparency.
Now, for each half-sample, choose which unit to take from each stratum according to the sign of the corresponding entry in H: that is, for half-sample h, we choose the first unit from stratum k if H hk = −1 and the second unit if H hk = +1. The orthogonality of rows of H ensures that our choices are uncorrelated between half-samples.
In the first example provided above, the sex of the patient would be a nuisance variable. For example, consider if the drug was a diet pill and the researchers wanted to test the effect of the diet pills on weight loss. The explanatory variable is the diet pill and the response variable is the amount of weight loss.