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8 variables and 25 observations

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Longitudinal study versus cross-sectional study?

A longitudinal study and a cross-sectional study are methods of collecting scientific data. A longitudinal study is the method that gathers data on a subject for a particular period of time and the subject's response to particular variables. A cross-sectional study is where more than one subject is used for the collection of data at different points in time in response to particular variables. These types of studies are sometimes used to determine correlation.


What is a alternative to a cross sectional study?

A longitudinal study is an alternative to a cross-sectional study. In a longitudinal study, data is collected from the same subjects over a period of time, allowing researchers to observe changes within individuals. This type of study provides a more in-depth understanding of how variables evolve over time compared to cross-sectional studies.


What is the major difference between a longitudinal study and cross sectional study?

the cross-sectional study selects a sample that has all the age ranges the researchers are interested in verses one group that is followed throught time


What has the author Gad Nathan written?

Gad Nathan has written: 'Multiplicity study of marriages and births in Israel' 'A review of sample attrition and representativeness in three longitudinal surveys'


Longitudinal in a sentence?

The study followed a group of individuals over a 10-year period to analyze changes in their cognitive abilities, which is an example of a longitudinal study.


What is a longitudinal cohort study?

A longitudinal cohort study is a research study where a group of participants is followed over an extended period of time to observe how certain variables or factors impact their health outcomes or behaviors. Researchers collect data at multiple time points to track changes over time and identify potential correlations and causations. This type of study design is commonly used in epidemiology and clinical research to understand the development and progression of diseases.


What is a sample study?

sample is the population we make our study about them.


What is the major difference between a longitudinal study and a cross sectional study?

the cross-sectional study selects a sample that has all the age ranges the researchers are interested in verses one group that is followed throught time


What is longitudinal research method?

Longitudinal research is a type of study where data is collected from the same subjects over a period of time to track changes or trends. This method allows researchers to observe how certain variables evolve or influence each other over time. Longitudinal studies are useful for understanding development, stability, and change in individuals or groups.


What is a longitude study?

A longitudinal study is a research design that involves repeated observations of the same variables over an extended period, often years or decades. This approach allows researchers to track changes and developments within the same subjects, making it particularly useful for studying trends, life events, and the long-term effects of certain variables. Longitudinal studies can be either observational or experimental and are often used in fields such as psychology, medicine, and social sciences.


What study design involves measuring the same participants over some period of time?

The study design that involves measuring the same participants over a period of time is called a longitudinal study. This approach allows researchers to track changes and developments in the same individuals, providing insights into trends and causal relationships over time. Longitudinal studies can be particularly useful in fields such as psychology, medicine, and social sciences to understand how variables evolve.


If you want to have a scientifically valid sample for a study you are doing?

To achieve a scientifically valid sample for your study, ensure that your sample is representative of the population you are investigating. This can be done through random sampling methods, which help eliminate bias and improve generalizability. Additionally, determine an appropriate sample size using statistical power analysis to ensure that your findings are reliable. Finally, consider stratifying your sample to account for key demographic variables that may influence the results.