1. Sample size Power Random allocation R.Raveendran

2. Why is sample size important?  Validity  Accuracy  Finance  Resources  Ethics

3. What factors will affect the size of the sample?  Degree of difference  Type I error  Type II error  Variation of data  Drop out  Non-compliance

4. What methods can be used to determine the sample size?  Arbitrary numbers ×  From previous studies ?  Nomograms & tables !  Formulas  Computer programs

5. How to calculate the sample size?  Assess the difference expected (0.5 kg)  Find out the SD of groups (0.4)  Set the level of significance (alpha - 0.05)  Set the beta level (0.02)  Select the appropriate formula (unpaired t)  Calculate the sample size u-v (diff/sd)/  Give allowances for drop-outs & non- compliance

6. Power Probability that a study can detect a difference Priori power determination : Power = 1 – beta Beta or type 2 error is the chances of missing a difference (false negative rate) Posteriori power calculation : Why? How? What is the implication?

7. Random Allocation Each unit in a sample has equal chance to be assigned a treatment  Simple  Block  Stratified  Cluster Treatment 1Treatment 2 3457834578 1 2 6 9 10

8. Thank you

9. Degree of difference The minimum difference that is clinically or practically important e.g. A drug reduces BP by 2 mm of Hg (120 to 118). Is it clinically important? What about 4 mm of Hg? What about 6? 10? 20? 30? 40? Implication – Large difference needs small sample size Small difference needs large sample size

10. Question : Is the rice cooked? Possible Results : + (Yes) - (No) True True False False Type I and II errors

11. Groups : Group A Vs B Question : Is there a difference between groups? Possible Results : + (Yes) - (No) True True False False True True False False Type I error = False + P Limit - 5% Type II error = False - P Limit - 20% Type I and II errors

12. Power Calculation Why? To find out whether a negative result is TRUE or FALSE How? Using the formula or computer programs What information is needed?  The difference (0.5)  Alpha (0.05)  Sample size and SD both groups (5, 5 & 0.29, 0.33)  Statistical test used (Unpaired t) Implication? No power; redo the experiment / no diff.