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Chi Square Test

Chi Square Test

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Chi Square Test

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  1. Chi Square Test Gitanjali Batmanabane

  2. 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.

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

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

  5. 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

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

  7. Contingency (2X2) table • Enter number of subjects – not percentages, ratios, averages etc., • Each subject can be entered only once

  8. 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. Total Total

  9. 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. Total 25 30 25 30 55 Total

  10. 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.