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I know how to do one way ANOVA when the response variable is continuous. I need help learning how to do one way ANOVA when the response variable is binary (i.e., how to calculate MSE within group and between groups when the response is binary).

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When your response is binary, you don't do an ANOVA. (For example, there is no within or between MSE.) Instead, you can do a chi-squared test, or you can fit a logistic regression model. Here is a simple example (with made up data), coded in R:

tab = as.table(matrix(c(12, 33, 19,
                        38, 17, 31 ), nrow=2, byrow=TRUE))
rownames(tab)        = c("Yes", "No")
names(dimnames(tab)) = c("y", "x")
tab
#      x
# y      A  B  C
#   Yes 12 33 19
#   No  38 17 31
chisq.test(tab)
#         Pearson's Chi-squared test
# X-squared = 18.695, df = 2, p-value = 8.716e-05
d = as.data.frame(tab)
d
#     y x Freq
# 1 Yes A   12
# 2  No A   38
# 3 Yes B   33
# 4  No B   17
# 5 Yes C   19
# 6  No C   31
lr.mod = glm(y~x, d, family=binomial, weights=Freq)
summary(lr.mod)
# ...
# Coefficients:
#             Estimate Std. Error z value Pr(>|z|)    
# (Intercept)   1.1527     0.3311   3.481 0.000499 ***
# xB           -1.8160     0.4458  -4.073 4.64e-05 ***
# xC           -0.6631     0.4410  -1.504 0.132701    
# ...
#     Null deviance: 204.71  on 5  degrees of freedom
# Residual deviance: 185.62  on 3  degrees of freedom
# ...
1-pchisq(q=(204.71 - 185.62), df=(5 - 3))
# [1] 7.155816e-05
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  • $\begingroup$ that is an excellent explanation, gung, what is the between group and within group MSE in this example? $\endgroup$ Commented Nov 25, 2015 at 1:31
  • $\begingroup$ @HeatherKeturah, there is no such thing. I tweaked my answer. $\endgroup$ Commented Nov 25, 2015 at 1:38
  • $\begingroup$ @HeatherKeturah, you certainly can run an ANOVA, you just use $0$s & $1$s as your y values, but it isn't valid to do so. I don't have time to read the paper now; I'm not sure what's going on there. $\endgroup$ Commented Nov 25, 2015 at 2:29

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