1. Statistics By Z S Chaudry

2. Why do I need to know about statistics ? • Tested in AKT • To understand Journal articles and research papers

3. Data • Qualitative (Descriptive) • Quantitative(Numeric) • Discrete • Continuous (range) • Mean/Median/Mode • Mean : Average • Median : middle value of data • Mode : Most Frequent occurring value

4. Distributions and Ranges • Gaussian distribution normal • Positively Skewed • Negatively Skewed • Range • Lower quartile • Upper quartile • Interquartile range – around median

5. Standard deviation – spread around mean • Square root of the variance • Variance = sum of the square deviations from the mean / n • 65% of values lie within 1 SD • 95% of values lie within 2 SD • 99% of values lie within 3 SD

6. Key Terms • Probability - likelihood or uncertainty of an event occurring • Add probabilities if EITHER/OR events • Multiply probabilities if AND events • Power • Related to size of study if study too small may not be able to detect a significant significance • Errors • Random Error • Systematic Error (bias)

7. Key Terms - contd • Hypothesis • Null hypothesis – NO DIFFERENCE between 2 groups under study • Rejecting Hypothesis when true –Type 1 error • Accepting Hypothesis when false – Type 2 error • Compare test results • T-test • Chi-squared test • Produce p-value • Probability of result occurring by chance alone • p<0.05 significant • p<0.01 highly significant

8. Key Terms - contd • Confidence interval • Level of uncertainty in following : • Odds ratios, relative risk,risk difference,sensitivity,specificity • The wider the range the less certain/significant the results • CI usually 95 % i.e. 2 SD from mean in either direction. • Provided study not biased true value can be expected to lie in the CI.

9. Key Terms - contd • The more people in a study the smaller the CI. • CI range including zero not statistically significant or if results expressed as ratios a CI including 1 is not statistically significant.

10. Measures of Risk • INCIDENCE – New cases • (New cases/population at risk over specific time) X 100 • PREVALENCE-Existing cases • (No of individuals with disease/population size during specific time) X 100

11. Measures of Association • Risk varies from 0 to 1 • Risk = probability of disease/death (R) • Risk = No with disease/no at risk of disease • Risk Difference = R1 – R2 • Relative Risk = R1/R2 • <1 intervention reduces risk of outcome • =1 no effect on outcome • >1 intervention increases risk of outcome • Absolute Risk = R1 – R2 / R2

12. ODDs and ODDs Ratios • Odds – ratio of probability of an event happening to that of it not happening • Odds Ratio – measure of effectiveness of treatment compared to control • OR = ODDs in treated grp/ODDs in control grp • <1 effects of treatment less than control group • =1 effect of treatment same as control group • >1 effect of treatment greater than control group

13. Diagnostic Testing • SENSITIVITY – Positive test /total number of positives • SPECIFICITY- Negative test when disease free • Positive Predictive Value – likelihood that positive test will be a true positive • Negative Predictive Value – likelihood that a negative test is a true negative • NNT= Number needed to treat = 1/ ARR So the smaller the ARR the greater the NNT

14. Bias • Publication –positive results more likely to be published • Selection – systematic differences between sample and target population. • Information – systematic errors in measures of outcome or exposure • ? Language – may be bias in inclusion of studies to be selected in meta-analysis.(combine results of several studies to answer a question)

15. Validity • Study validity • Internal and external bias • Internal validity • Extent to which conclusions in a study are legitimate. • External validity • Degree to which conclusions generated from a study can be generalised to a target population.

16. Study designs • Experimental • RCT • Cohort • Longitudinal follow-up of 2 or more groups with recorded exposure to risk • Provides comparative incidence estimates between groups • Can have surveillance bias • Case controlled • Used when prevalence low

17. Study designs • Observational • Cross-sectional • Gives prevalence estimates

18. Forest plots • Pictorial representation of ODDs ratios in form of a horizontal line • If horizontal line crosses vertical line results are not significant! • Horizontal line represents the 95% CI of each trial being plotted

19. Further Reading • High-Yield Biostatistics by Lippincott Williams and Wilkins • The Complete nMRCGP Study Guide by Sarah Gear • CASP tools – Critical Analysis to review papers – available on the web

20. THE END THANK YOU