A cross-sectional study is a type of observational study, or descriptive research, that involves analyzing information about a population at a specific point in time. Typically, these studies are used to measure the prevalence of health outcomes and describe characteristics of a population.
What is a cross-sectional correlational study?
Cross-sectional studies – These are considered a type of cohort study where only one comparison is made between exposed and unexposed subjects. They provide a snapshot of the outcome and the associated characteristics of the cohort at a specific point in time.
What is a cross-sectional study example?
Another example of a cross-sectional study would be a medical study examining the prevalence of cancer amongst a defined population. The researcher can evaluate people of different ages, ethnicities, geographical locations, and social backgrounds.
What sampling method is used for cross-sectional study?
You can use stratified random sampling then simple random sampling for each strata of undergraduate students.
What is the main purpose of a cross-sectional study? – Related Questions
Is a cross-sectional correlational study quantitative?
Most cross-sectional studies are quantitative. They gather data through interviews, questionnaires, and focus groups over a certain period in time which may be in the past or the present, and then analyze the results.
Can cross-sectional studies show correlation?
Cross-sectional studies can identify potential correlations, associations and relationships between variables. However, often they cannot define direct causation.
What is a descriptive cross-sectional correlational design?
A descriptive cross-sectional study is a study in which the disease or condition and potentially related factors are measured at a specific point in time for a defined population.
What type of study design is a correlational study?
A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research.
How do you tell if a study is experimental or correlational?
What’s the difference between correlational and experimental research?
- In an experimental design, you manipulate an independent variable and measure its effect on a dependent variable.
- In a correlational design, you measure variables without manipulating any of them.
How do you tell if a study is correlational or causal?
Theoretically, the difference between the two types of relationships are easy to identify — an action or occurrence can cause another (e.g. smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. smoking is correlated with alcoholism, but it does not cause alcoholism).
What are the 3 types of correlation?
Types of Correlation
- Positive Linear Correlation. There is a positive linear correlation when the variable on the x -axis increases as the variable on the y -axis increases.
- Negative Linear Correlation.
- Non-linear Correlation (known as curvilinear correlation)
- No Correlation.
Should I use Pearson or Spearman correlation?
One more difference is that Pearson works with raw data values of the variables whereas Spearman works with rank-ordered variables. Now, if we feel that a scatterplot is visually indicating a “might be monotonic, might be linear” relationship, our best bet would be to apply Spearman and not Pearson.
What is the difference between Pearson and Spearman correlation?
Pearson correlation: Pearson correlation evaluates the linear relationship between two continuous variables. Spearman correlation: Spearman correlation evaluates the monotonic relationship. The Spearman correlation coefficient is based on the ranked values for each variable rather than the raw data.
What statistical test is used for correlations?
Pearson’s correlation coefficient (r) is used to demonstrate whether two variables are correlated or related to each other.
Is ANOVA used for correlation?
ANOVA like regression uses correlation, but it constrols statistically for other independent variables in your model by focusing on the unique variation in the DV explained by the IV. That is the covariation between a IV and DV not explained by any other IV.
Which is better chi-square or Spearman?
If you want to find monotonic association, the Spearman will tend to have much better power than the chi-squared test. If you want to find more general kinds of association, then the chi-squared test will be able to detect associations that the Spearman cannot.
Which statistical test should I use psychology?
In the field of psychology, statistical tests of significances like t-test, z test, f test, chi square test, etc., are carried out to test the significance between the observed samples and the hypothetical or expected samples.
What is the most commonly used statistical in psychology?
The most common statistical tests include the student’s T-test and the Analysis of Variance (or F-test); these statistics help the psychologist assess whether the differences in averages across groups are due to the effects of an independent variable.
What is the most accurate psychology test?
The Big Five Personality Test is by far the most scientifically validated and reliable psychological model to measure personality. This test is, together with the Jung test (MBTI test style) and the DISC assessment, one of the most well known personality tests worldwide.
What is the most widely used test in psychological research?
The Minnesota Multiphasic Personality Inventory, Second Edition (MMPI-2) is a written psychological assessment used to diagnose mental disorders; it is the most widely used and widely researched test of adult psychopathology.
