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For example, experiments in which each condition takes only a few minutes, whereas the training to complete the tasks take as much, if not more time. Longitudinal analysis—Repeated measure designs allow researchers to monitor how participants change over time, both long- and short-term situations.
In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions. It is a crucial step to test the original claim and confirm or reject the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]
Short tandem repeat (STR) analysis is a common molecular biology method used to compare allele repeats at specific loci in DNA between two or more samples. A short tandem repeat is a microsatellite with repeat units that are 2 to 7 base pairs in length, with the number of repeats varying among individuals, making STRs effective for human ...
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 disadvantage of this method is that some observations may never be selected in the validation subsample, whereas others may be selected more than once. In other words, validation subsets may overlap. This method also exhibits Monte Carlo variation, meaning that the results will vary if the analysis is repeated with different random splits.
There are different reasons for performing a round-robin test: determination the reproducibility of a test method or process; verification of a new method of analysis. If a new method of analysis has been developed, a round-robin test involving proven methods would verify whether the new method produces results that agree with the established method.
In statistics, one-way analysis of variance (or one-way ANOVA) is a technique to compare whether two or more samples' means are significantly different (using the F distribution). This analysis of variance technique requires a numeric response variable "Y" and a single explanatory variable "X", hence "one-way".
The one-factor-at-a-time method, [1] also known as one-variable-at-a-time, OFAT, OF@T, OFaaT, OVAT, OV@T, OVaaT, or monothetic analysis is a method of designing experiments involving the testing of factors, or causes, one at a time instead of multiple factors simultaneously.