Contents
What is a follow up analysis for chi-square?
Another chi-square topic concerns follow-up or post hoc tests when a larger contingency table (e.g., 3 X 3) is analyzed. Just like with the ANOVA test, the chi-square test is an “omnibus” test, because it is an overall test to see if there are differences between any of the cell frequencies.
Why is it necessary to perform a follow up analysis to a chi-square test?
If the test allows us to reject the null hypothesis of no difference, we then want to do a follow up analysis that examines the differences in detail. State the null and alternative hypotheses for a Chi-square test for Association/Independence.
When to use the chi square distribution table?
The Chi-square distribution table is a table that shows the critical values of the Chi-square distribution. To use the Chi-square distribution table, you only need two values: A significance level (common choices are 0.01, 0.05, and 0.10) Degrees of freedom. The Chi-square distribution table is commonly used in the following statistical tests:
What to use instead of chi-squared in a contingency table?
Had this been a 2×2 contingency table instead of a 3×3, I know that a chi-squared test would have given me the answer. For instance, a non-significant Yates-corrected χ2 would have suggested that subjects are answering by chance. I’m not sure, however, what test I need to use for this 3×3 contingency table.
How to find the chi square critical value?
If you are interested in finding the Chi-square critical value for a given significance level and degrees of freedom, then you should use the Chi-square Distribution Table.
What to use instead of chi-squared test?
3×3 contingency table: what to use instead of chi-squared test? I have questionnaire data from subjects divided into 3 groups, G1, G2 and G3. Subjects had to answer a question, and they had the options A1, A2 or A3 to choose from.