McNemar

Paired yes/no answers, before and after.

When should I use McNemar?

Each participant was classified twice, so the two counts are linked and a chi-square test would treat them as though they came from different people. McNemar's test looks only at the participants who changed, which is where the evidence of a change actually is.

What your data needs to look like

A table of counts — how many people fall into each category, not percentages.

What Chavery does with it

It checks the assumptions first and says whether each one held. When an assumption fails it names the alternative test rather than running this one anyway.

Then it reports the statistic, the p-value, a confidence interval and an effect size, and writes the sentence you would put in your results chapter. The same numbers always give the same answer; nothing is generated by a language model.

Reporting it

A p-value on its own is not a result. Chavery reports the effect size beside it, because a difference can be statistically significant and too small to matter, and an examiner will ask which yours is. More on effect size.

Not sure this is the test you need? Work through the question Chavery asks and it will name the test your design calls for.

Related tests

• Chi-square — Is a category associated with an outcome?
• Fisher's exact — A 2x2 table with small counts.