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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]
Cross-sectional study: involves data collection from a population, or a representative subset, at one specific point in time. Longitudinal study: correlational research study that involves repeated observations of the same variables over long periods of time. Cohort study and Panel study are particular forms of longitudinal study.
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.
Cross-sectional research is a research method often used in developmental psychology, but also utilized in many other areas including social science and education. This type of study utilizes different groups of people who differ in the variable of interest, but share other characteristics such as socioeconomic status, educational background ...
Quantitative psychological research findings result from mathematical modeling and statistical estimation or statistical inference. The two types of research differ in the methods employed, rather than the topics they focus on. There are three main types of psychological research: Correlational research; Descriptive research; Experimental research
Since correlation does not imply causation, such studies simply identify co-movements of variables. Correlational designs are helpful in identifying the relation of one variable to another, and seeing the frequency of co-occurrence in two natural groups (see Correlation and dependence). The second type is comparative research. These designs ...
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 ...
Cross-sectional data differs from time series data, in which the same small-scale or aggregate entity is observed at various points in time. Another type of data, panel data (or longitudinal data ), combines both cross-sectional and time series data aspects and looks at how the subjects (firms, individuals, etc.) change over a time series.