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The cross-sectional study has the advantage that it can investigate the effects of various demographic factors (age, for example) on individual differences; but it has the disadvantage that it cannot find the effect of interest rates on money demand, because in the cross-sectional study at a particular point in time all observed units are faced ...
Cross-sectional data can be used in cross-sectional regression, which is regression analysis of cross-sectional data. For example, the consumption expenditures of various individuals in a fixed month could be regressed on their incomes, accumulated wealth levels, and their various demographic features to find out how differences in those ...
In statistics and econometrics, a cross-sectional regression is a type of regression in which the explained and explanatory variables are all associated with the same single period or point in time. This type of cross-sectional analysis is in contrast to a time-series regression or longitudinal regression in which the variables are considered ...
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.
In cross-sectional studies, a sample (or samples) is drawn from the relevant population and studied once. [3] A cross-sectional study describes characteristics of that population at one time, but cannot give any insight as to the causes of population characteristics because it is a predictive, correlational design.
The design of a study defines the study type (descriptive, correlational, semi-experimental, experimental, review, meta-analytic) and sub-type (e.g., descriptive-longitudinal case study), research problem, hypotheses, independent and dependent variables, experimental design, and, if applicable, data collection methods and a statistical analysis ...
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 ...
A literature search often involves time series, cross-sectional, or panel data. Cross-panel data (CPD) is an innovative yet underappreciated source of information in the mathematical and statistical sciences. CPD stands out from other research methods because it vividly illustrates how independent and dependent variables may shift between ...