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8 maj 2020 · A cross-sectional study is a type of research design in which you collect data from many different individuals at a single point in time. In cross-sectional research, you observe variables without influencing them.
9 lip 2024 · In cross-sectional studies, participants are chosen according to the inclusion and exclusion criteria established in the study without considering exposure (independent variable) or outcome status (dependent variable) in the selection of the study population.
3 lut 2022 · An independent variable is the variable you manipulate or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.
10 paź 2021 · The cross-sectional design is an appropriate method to determine the prevalence of a disease, attribute, or phenomena in a study sample. The design provides a ‘snapshot” of the sample, and investigators can describe their study sample and review associations between the collected variables (independent and dependent).
4 sty 2024 · In this section, we specifically address the elements that make cross-sectional a discrete research design. Next to the characteristics of cross-sectional studies, we address the main issues and decisions to be made within this research design and the major pitfalls.
10 lis 2021 · A cross-sectional study aims at describing generalized relationships between distinct elements and conditions. The specific case and its particularities are not the focus, but all instances and cases. So cross-sectional studies try to establish general models that link a combination of elements with other elements under certain conditions.
Cross-Sectional Study Design and Data Analysis. SUBJECT AREA: Statistics, mathematics, biology. OBJECTIVES: At the end of this module, students will be able to: Explain the cross-sectional study design. Understand the process of questionnaire construction. Identify several sampling strategies.
