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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 ]
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. [1]
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.
Balanced repeated replication is a statistical technique for estimating the sampling variability of a statistic obtained by stratified sampling. Outline of the technique [ edit ]
repetition over a short period of time. same objectives; Repeatability methods were developed by Bland and Altman (1986). [5] If the correlation between separate administrations of the test is high (e.g. 0.7 or higher as in this Cronbach's alpha-internal consistency-table [6]), then it has good test–retest reliability.
In particular, the bootstrap is useful when there is no analytical form or an asymptotic theory (e.g., an applicable central limit theorem) to help estimate the distribution of the statistics of interest. This is because bootstrap methods can apply to most random quantities, e.g., the ratio of variance and mean.
Replication (scientific method), one of the main principles of the scientific method, a.k.a. reproducibility Replication (statistics), the repetition of a test or complete experiment; Replication crisis; Self-replication, the process in which an entity (a cell, virus, program, etc.) makes a copy of itself
In statistics, the two-way analysis of variance (ANOVA) is an extension of the one-way ANOVA that examines the influence of two different categorical independent variables on one continuous dependent variable. The two-way ANOVA not only aims at assessing the main effect of each independent variable but also if there is any interaction between them.