ANOVA for yes/no data? Urgent!
By - Kabidon
I would choose chi square analysis. UCLA has a good guide for choosing tests and how to run them in various programs (SPSS, R, etc.). https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
Also, that was under the assumption the conditions are between-subjects.
Would chi square allow me to compare:
Group 2 to group 1
Then group 3 to group 1
Then group 4 to groups 1 and 2
1=control, 2&3=manipulations, 4=mixed manipulations.
How would this work in spss?
So unfortunately the chi square test can only tell you whether the nature of one variable—in this case, a yes or no answer—depends on another (the 4 conditions). If you want to compare groups, you could try logistic regression with dummy variables. This article can guide you through it: https://stats.idre.ucla.edu/spss/output/logistic-regression/ you can also try YouTube, there are lots of video tutorials on logistic regression, dummy variables, and interpreting odds ratios. Best of luck!
Binomial logistic regression
I feel like a chi-square analysis would be better suited for binary variables. Although from the top of my head I can't think of a reason why a between-subjects ANOVA followed by post-hoc tests wouldn't be a viable solution.
In SPSS chi-square can be performed using the crosstabs option.
Because one of the assumptions of an ANOVA is that your dependent variable is on an interval or ratio scale.
So you can’t use an ANOVA with yes/no data as yes/no decisions are on the nominal scale.
So OP chi-square analyses or binary logistic regression are your best bets.
This stuff isn’t fresh for me, but I think that’s a factorial ANOVA? Within,between or mixed.
Factorial ANOVA would be appropriate if there were multiple independent variables. In this case, there are four levels of *one* factor.
“Between groups” I'd say? bc you are comparing the number of “yes” answers in each group to the other groups.
My brother has a case like this and we chose to use chi-square (we thought of mcnemar first but it didnt work). ANOVA (to the best of my knowledge) is use when you want to compare a continous variable with another that is more than 2 groups. What is your exposure variable btw?
Chi squared goodness of fit?