| Age | SPH_i | SPH_f | CYL_i | CYL_f | gender |
|---|---|---|---|---|---|
| 8 | -2.00 | -0.25 | 0.00 | 0.00 | F |
| 8 | -4.25 | -0.50 | 0.00 | -0.25 | F |
| 8 | -3.75 | -0.75 | 0.00 | -0.25 | M |
| 8 | -1.75 | -0.25 | 0.00 | -0.25 | M |
| 8 | -1.50 | 0.00 | -0.50 | -0.50 | F |
| 9 | -4.50 | -1.00 | -1.50 | -0.25 | F |
| 9 | -3.50 | -0.75 | -0.50 | 0.00 | F |
| 9 | -2.50 | -0.25 | 0.00 | -0.25 | F |
| 10 | -1.00 | 0.00 | 0.00 | -0.25 | F |
| 10 | -2.25 | -0.25 | 0.00 | 0.00 | F |
| 10 | -2.75 | -0.25 | 0.00 | 0.00 | F |
| 10 | -4.00 | -0.25 | -0.50 | 0.00 | F |
| 10 | -3.25 | -0.50 | -0.50 | -0.25 | M |
| 10 | -3.50 | 0.00 | -0.75 | 0.00 | M |
| 10 | -4.00 | -1.25 | 0.00 | -0.25 | M |
| 10 | -2.00 | -0.25 | -0.50 | 0.00 | M |
| 10 | -1.00 | 0.00 | 0.00 | 0.00 | M |
| 10 | -2.25 | 0.00 | 0.00 | 0.00 | F |
| 10 | -4.00 | -0.50 | 0.00 | 0.00 | F |
| 11 | -4.50 | -0.50 | -0.50 | -0.50 | F |
| 11 | -5.00 | -0.25 | -0.75 | -0.50 | M |
| 11 | -3.25 | -0.75 | -0.75 | 0.00 | M |
| 12 | -2.50 | 0.00 | 0.00 | 0.00 | F |
| 12 | -3.25 | -0.50 | -0.50 | -0.25 | M |
| 12 | -1.25 | -0.25 | -0.75 | 0.00 | M |
| 13 | -5.75 | -0.75 | -0.75 | -0.50 | M |
| 13 | -6.00 | -0.50 | -0.50 | -0.50 | M |
| 13 | -4.00 | -0.25 | -1.50 | -0.50 | M |
| 13 | -1.00 | 0.00 | -0.75 | -0.50 | F |
| 14 | -5.00 | -0.50 | -1.25 | -0.25 | F |
| 14 | -6.25 | -0.75 | -1.50 | -0.25 | F |
| 14 | -5.50 | -0.25 | 0.00 | 0.00 | M |
| 14 | -3.25 | -0.25 | 0.00 | -0.25 | F |
| 14 | -3.50 | -0.50 | -0.50 | -0.25 | M |
Methodology
Procedure
- Get raw data from NCBI, download spreadsheet by clicking the link in supplementary information (Yin et at., 2019)
- Use the column of age, gender, spherical diopter (SPH) and cylinder diopter (CYL) in the spreadsheet to generate a new raw data table.
- Process the data to calculate the initial, final and change in SE (D) and the percent improvement of SE (%) for each patient, respectively.
- Plot a graph based on the percent improvement of SE (%) of each patient.
- Generate a null hypothesis and an alternative hypothesis for justification, then use statistical analysis (modelling and Pearson’s correlation coefficient) to find whether there is a correlation between IV (patients’ initial treatment age) and DV (percent improvement of SE (%)), then evaluate whether the relationship is statistically significant.
- Draw conclusions based on processed data and statistical analysis.
Data Treatment
Raw data table
Calculations
Initial SE (D): \[SE_i = SPH_i + 1/2CYL_i\] Final SE (D): \[SE_f = SPH_f + 1/2CYL_f\] Delta SE (D) after 1 year of treatment: \[SE_d = SE_f - SE_i\] Percent improvement of SE (%): \[SE_i = SPH_i + 1/2CYL_i\]
Processed data table
| Age | gender | SE_i | SE_f | SE_d | SE_improve |
|---|---|---|---|---|---|
| 8 | F | -2.000 | -0.250 | 1.750 | 0.8750000 |
| 8 | F | -4.250 | -0.625 | 3.625 | 0.8529412 |
| 8 | M | -3.750 | -0.875 | 2.875 | 0.7666667 |
| 8 | M | -1.750 | -0.375 | 1.375 | 0.7857143 |
| 8 | F | -1.750 | -0.250 | 1.500 | 0.8571429 |
| 9 | F | -5.250 | -1.125 | 4.125 | 0.7857143 |
| 9 | F | -3.750 | -0.750 | 3.000 | 0.8000000 |
| 9 | F | -2.500 | -0.375 | 2.125 | 0.8500000 |
| 10 | F | -1.000 | -0.125 | 0.875 | 0.8750000 |
| 10 | F | -2.250 | -0.250 | 2.000 | 0.8888889 |
| 10 | F | -2.750 | -0.250 | 2.500 | 0.9090909 |
| 10 | F | -4.250 | -0.250 | 4.000 | 0.9411765 |
| 10 | M | -3.500 | -0.625 | 2.875 | 0.8214286 |
| 10 | M | -3.875 | 0.000 | 3.875 | 1.0000000 |
| 10 | M | -4.000 | -1.375 | 2.625 | 0.6562500 |
| 10 | M | -2.250 | -0.250 | 2.000 | 0.8888889 |
| 10 | M | -1.000 | 0.000 | 1.000 | 1.0000000 |
| 10 | F | -2.250 | 0.000 | 2.250 | 1.0000000 |
| 10 | F | -4.000 | -0.500 | 3.500 | 0.8750000 |
| 11 | F | -4.750 | -0.750 | 4.000 | 0.8421053 |
| 11 | M | -5.375 | -0.500 | 4.875 | 0.9069767 |
| 11 | M | -3.625 | -0.750 | 2.875 | 0.7931034 |
| 12 | F | -2.500 | 0.000 | 2.500 | 1.0000000 |
| 12 | M | -3.500 | -0.625 | 2.875 | 0.8214286 |
| 12 | M | -1.625 | -0.250 | 1.375 | 0.8461538 |
| 13 | M | -6.125 | -1.000 | 5.125 | 0.8367347 |
| 13 | M | -6.250 | -0.750 | 5.500 | 0.8800000 |
| 13 | M | -4.750 | -0.500 | 4.250 | 0.8947368 |
| 13 | F | -1.375 | -0.250 | 1.125 | 0.8181818 |
| 14 | F | -5.625 | -0.625 | 5.000 | 0.8888889 |
| 14 | F | -7.000 | -0.875 | 6.125 | 0.8750000 |
| 14 | M | -5.500 | -0.250 | 5.250 | 0.9545455 |
| 14 | F | -3.250 | -0.375 | 2.875 | 0.8846154 |
| 14 | M | -3.750 | -0.625 | 3.125 | 0.8333333 |