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Rather than studying particular individuals across that whole period of time (e.g. 20–60 years) as in a longitudinal design, or multiple individuals of different ages at one time (e.g. 20, 25, 30, 35, 40, 45, 50, 55, and 60 years) as in a cross-sectional design, the researcher chooses a smaller time window (e.g. 20 years) to study multiple ...
In medical research, epidemiology, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data. [definition needed]
In medicine, a crossover study or crossover trial is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). While crossover studies can be observational studies, many important crossover studies are controlled experiments, which are discussed in this article.
It is also common to use the multivariate η 2 when the assumption of sphericity has been violated, and the multivariate test statistic is reported. A third effect size statistic that is reported is the generalized η 2, which is comparable to η p 2 in a one-way repeated measures ANOVA. It has been shown to be a better estimate of effect size ...
Microgenetic design (a.k.a. microgenetic method) is a scientific method in which the same setting is studied repeatedly in order to observe change in detail.In contrast to cross-sectional and longitudinal designs, which provide broad outlines of the process of change, microgenetic designs provide an in-depth analysis of the behavior of the system while it is changing.
Cross-sequential study: Groups of different ages are studied at multiple time points; combines cross-sectional and longitudinal designs; Research in psychology has been conducted with both animals and human subjects: Animal study; Human subject research
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
An example of an epidemiological question that can be answered using a cohort study is whether exposure to X (say, smoking) associates with outcome Y (say, lung cancer). For example, in 1951, the British Doctors Study was started. Using a cohort which included both smokers (the exposed group) and non-smokers (the unexposed group).
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