The data consists of a control and the measurements taken at 2 weeks, then another control and measurements taken at 4 weeks. The data is for 2 groups so there's 2 sets of data for the different weeks.
My results will be looking at the changes in the different weeks (week 4 showing larger measurements than week 2 with both being higher than the controls) and then comparing the 2 different groups at week 2 and week 4.
I need to do statistical analysis for the controls vs the measurements and another comparing the 2 groups for the same week. The groups show similar values but I need to determine if they're significant.
For context: The research is observing the collagen in heart tissue increasing from week 2 to week 4 in a diabetic animal model. Image analysis measurements were taken using 2 different stains to see how they compare when measuring the collagen content at the different weeks.
Based on your description, it sounds like you are interested in comparing the mean measurements between the control and experimental groups at different time points. To do this, you can use a two-way ANOVA with repeated measures. This type of analysis allows you to assess the main effects of group and time, as well as the interaction between group and time. In addition to the ANOVA, you can perform post-hoc tests to determine whether there are significant differences between the groups at specific time points. Common post-hoc tests include Tukey's Honestly Significant Difference (HSD) test or Scheffe's test.
Regards,
Based on the information provided, it seems that a paired t-test and an independent samples t-test may be appropriate for analyzing your data.
For comparing the control and measurements within each group at different time points (week 2 vs. control, week 4 vs. control), you can use a paired t-test. This will determine if there is a significant difference in measurements between the control and each time point within each group.
For comparing the two groups at each time point (week 2 and week 4), you can use an independent samples t-test. This will determine if there is a significant difference in measurements between the two groups at each time point.
To conduct these tests, you can use statistical software such as SPSS or R. Your software should have functions to perform these tests and output the results, including the p-value and significance level. It is important to interpret these results carefully and to report your findings in a clear and concise manner in your scientific report.
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