Looking for Appropriate Test to Use

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In summary, the researcher is considering using a multi-factorial ANOVA to test the effect of multiple independent variables (age, gender, sport, and position) on six dependent variables (BET, OET, BIT, OIT, NAR, RED) in a study with 75 varsity athletes. This approach is appropriate for determining differences in scores based on the independent variables.
  • #1
Dants
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Hello again,

I swear ... I seem to struggle trying to decipher which ANOVA to use ... drives me crazy.

In this study, I have 75 participants that are all varsity athletes. They all completed a survey that scored attentional style within 6 variables (BET, OET, BIT, OIT, NAR, RED).

I am looking to see if there is any difference between the participants scores and the sports they play as well as the position they play in that sport. I was also considering to see if there is a difference between male and female scores as well as if there is a difference within age of participants.

I am considering doing a Multi-factorial ANOVA and applying my independent variables (age, gender, sport and position) to each dependent variable (BET, OET, BIT, OIT, NAR, RED) separately. Am I correct in doing it this way?

Please helpppppppp :/
 
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  • #2
Yes, this is the correct approach to take. A multi-factorial ANOVA allows you to test for the effect of multiple independent variables on one or more dependent variables. By running separate tests for each of the dependent variables, you can determine if there is a difference in scores based on the independent variables.
 

Related to Looking for Appropriate Test to Use

What is the purpose of looking for an appropriate test to use?

The purpose of looking for an appropriate test to use is to ensure that the data collected is accurately and effectively analyzed. Different tests have different strengths and limitations, and choosing the right test can lead to more reliable and valid results.

What factors should be considered when selecting a test?

When selecting a test, factors such as the type of data being collected, the research question or hypothesis, the sample size, and the level of measurement should be considered. It is also important to consider the assumptions and requirements of the chosen test.

Can the same test be used for different types of data?

No, different types of data require different tests for accurate analysis. For example, categorical data may require a chi-square test while continuous data may require a t-test or ANOVA. It is important to choose a test that is appropriate for the type of data being analyzed.

What happens if the chosen test is not appropriate for the data?

If the chosen test is not appropriate for the data, the results may be inaccurate and misleading. This can lead to incorrect conclusions and implications. It is important to carefully consider the data and choose the most appropriate test for accurate analysis.

Are there any resources available to help choose an appropriate test?

Yes, there are many resources available to help choose an appropriate test. These include statistical textbooks, online guides, and consulting with a statistician. It is important to carefully review and understand the assumptions and requirements of the chosen test before conducting any analysis.

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