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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 ...
There are many ways to classify research designs. Nonetheless, the list below offers a number of useful distinctions between possible research designs. A research design is an arrangement of conditions or collection. [5] Descriptive (e.g., case-study, naturalistic observation, survey) Correlational (e.g., case-control study, observational study)
Research design Utility Potential analysis Between-group design: Experiment that has two or more groups of subjects each being tested by a different testing factor simultaneously: Student's t-test, Analysis of variance, Mann–Whitney U test: Repeated measures design
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.
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] For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
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]
Huck, S. W. & McLean, R. A. (1975). "Using a repeated measures ANOVA to analyze the data from a pretest-posttest design: A potentially confusing task". Psychological Bulletin, 82, 511–518. Pollatsek, A. & Well, A. D. (1995). "On the use of counterbalanced designs in cognitive research: A suggestion for a better and more powerful analysis".