Fastbleep Academic Masterclass N

1. Using Statistical tests Richard Salisbury richardasalisbury@gmail.com

2. What I’m going to cover Key concepts What test when? Examples

3. Key concept 1: The null hypothesis I predict that any difference seen between two groups is due to chance alone. Use 95% cut off in medicine P > 0.05 = accept null hypothesis P < 0.05 = reject null hypothesis as difference is NOT due to chance. There is a statistically significant difference between groups.

4. Key concept 2: Data types Continuous eg. height Discrete - integers Ordinal - ranked Categorical eg. Hair colour Dichotomous/Binary eg. Yes/no

5. Key concept 3: Normal/Gaussian distribution Cumulative frequency Mean =median=mode Value Central Limit Theorem Shapiro Wilk test

6. Common statistical tests

7. Chi-squared test Which test to use? Yes Is data categorical? No Mann-Whitney U test Is data normally distributed? No 2 groups or less? Yes No Yes Is n > 30 ANOVA No Yes T-test Z-test

8. Chi-squared test Which test to use? Yes Is data categorical? No Mann-Whitney U test Is data normally distributed? No 2 groups or less? Yes No Yes Is n > 30 ANOVA No Yes T-test Z-test

9. Normally distributed data - T-test Comparison of means taking into account spread Allows comparison 2 groups OR a comparison of one group and an expected mean 1 tailed Vs 2 tailed – what question are you asking? Independent groups Vs Dependent/Paired groups

10. Example 1 I have audited BMI of 20 patients undergoing gastric banding, I want to compare this with the national average. Data - BMI is a continuous variable and therefore will be normally distributed about the mean. Groups - 2 groups Number - n<30 T-test using mean and variance of my group compared to mean and variance of national average. 2 tail t-test as I am interested in knowing whether the BMI is different therefore either smaller or larger 1 tail t-test could be used if I wanted to ask is the BMI larger in patients undergoing gastric banding compared to national average

11. Example 2 Does CBT change the mood (measured by visual analogue scale) of 50 depressed individuals? – Comparison of before and after scores Data – Normally distributed Groups – 2; before Vs after CBT Number – n>30 BUT groups are not independent – repeated measures 2-tail paired T-test 1-tail paired t-test would be for a question that asks if CBT increases mood.

12. Alternatives to t-test Z-test for independent variables where n > 30 ANOVA for more than 2 groups – multiple comparisons (the more comparisons you do, the more likely you are to get a false positive) ANOVA tests for difference between all groups A post test egBonferroni then tests for differences between individual groups Eg. RCT Placebo Vs Drug A Vs Drug B

13. Chi-squared test Which test to use? Yes Is data categorical? No Mann-Whitney U test Is data normally distributed? No 2 groups or less? Yes No Yes Is n > 30 ANOVA No Yes T-test Z-test

16. Chi squared and Fisher’s exact test Used to compare categorical data against expected data (probabilities eg. Mendellian crosses) OR against other independent categorical data. Fisher’s exact test is more accurate, especially if n is small, but is harder to calculate.

17. Regression Analysis Compares how an independent variable changes the value of a dependent variable, independent of any other independent variables. This is as complicated as it sounds. Seek help early!

18. Examples to finish

20. Example 2 (Siregar P, Setiati S., Urine osmolality in the elderly. Acta Med Indones. 2010 Jan;42(1):24-6.) A study recorded the urine osmolality of 13 and 15 respectively female and male elderlies. Objective: is the urine osmolality different in males and females?

22. Variable: urine osmolality

24. Questions