Chi Square Test Gitanjali Batmanabane Gitanjali 1 At

Chi Square Test Gitanjali Batmanabane Gitanjali 1

At the end of this session you will be able to: Prepare a contingency table Realise which study designs are suitable for applying the chi square test Understand the assumptions / limitations of the chi square test. Gitanjali 2

Know thyself Gitanjali 3 Why does he keep saying this all the time?

No, my son, but I understand something about this “NOT KNOWING” Gitanjali 4 Excuse me sir, you say “know yourself” all the time but do YOU KNOW YOURSELF?

What is it? Test of proportions Non parametric test Dichotomous variables are used Tests the association between two factors e. g. treatment and disease gender and mortality Gitanjali 5

Associations and Causal Associations Relationship between variables Not statistically associated Statistically associated Non-causal Gitanjali 6 Indirectly causal Causal Directly causal

Contingency (2 X 2) table Exposure Outcome Yes No Enter number of subjects – not percentages, ratios, averages etc. , v Gitanjali 7 v Each subject can be entered only once

Out of 25 women who had uterine cancer, 20 claimed to have used estrogens. Out of 30 women without uterine cancer 5 claimed to have used estrogens. Exposure (estrogen) Yes No Gitanjali 8 Total Outcome (cancer) Yes No Total

Out of 25 women who had uterine cancer, 20 claimed to have used estrogens. Out of 30 women without uterine cancer 5 claimed to have used estrogens. Exposure Gitanjali 9 Outcome Total Yes No Yes 20 5 25 No 5 25 30 Total 25 30 55

Assumptions / Limitations Data is from a random sample. A sufficiently large sample size is required (at least 20) Actual count data (not percentages) Adequate cell sizes should be present. (>5 in all cells- if less number present apply Yates correction) Observations must be independent. Does not prove causality. Gitanjali 10