To include statistics at two levels on GraphPad Prism, you need to account for both the within-patient (intra-patient) and between-patient (inter-patient) variability. Here’s how you can approach this:

Step 1: Organize Your Data

You have 7 patients for both control and treatment groups, with 5 measurements per patient. Structure your data in two levels:

1. Level 1 (Intra-patient): The 5 measurements for each patient.

2. Level 2 (Inter-patient): The mean of the 5 measurements for each patient.

Step 2: Input Data in GraphPad Prism

1. Create a new data table: Choose the appropriate format for your data. In this case, you can use a nested design.

2. Enter your data:

- Each row represents a patient.

- Each column represents one of the 5 measurements for that patient.

Step 3: Perform Nested ANOVA

GraphPad Prism allows you to perform a nested ANOVA, which is suitable for your hierarchical data structure.

1. Go to the 'Analyze' menu: Select 'Nested t test or ANOVA' under the 'Grouped analyses'.

2. Set up the analysis:

- Choose the option that your data are arranged by row (each row is a patient).

- Specify that you have nested data with repeated measures.

Step 4: Configure the Nested ANOVA

1. Define your groups: Control and treatment groups.

2. Specify the nested structure: Measurements nested within patients.

Step 5: Interpret the Results

GraphPad Prism will provide you with:

- The within-group (intra-patient) variation.

- The between-group (inter-patient) variation.

- Statistical significance for both levels.

Step 6: Visualize the Data

You can represent your data graphically with 7 points for control and 7 points for treatment:

1. Create a scatter plot: Plot the mean values for each patient.

2. Add error bars: Represent the SEM for each patient's mean.

Example of a Nested ANOVA Analysis

Here’s a step-by-step example:

1. Data Input: Enter your data in a table like this as you can find attached:

2. Run Nested ANOVA: Analyze > Nested t test or ANOVA.

3. Set Parameters: Choose 'Groups' for control and treatment. Define the nesting of measurements within patients.

4. Plot the Data: Create a scatter plot with the means of each patient's measurements. Add error bars to show the SEM of the five measurements per patient.

This approach will allow you to include both the means and SEM of the five countings per patient, providing a more comprehensive statistical analysis of your data.

For more detailed guidance, you can refer to GraphPad Prism's user manual or support resources on nested analyses and data visualization.

thank you so much David Nkem for your very complete and easy to understand answer to my question !