fit4 <- glm(categorical_FOD_FODs ~ 0 + Condition_FODs:nativelang_FODs - 1, family = binomial(link = 'logit'), data = indvar_FODs) summary(fit4) Condition_FODsA:nativelang_FODsDanish -3.185e-01 4.647e-01 -0.685 0.4931 Condition_FODsB:nativelang_FODsDanish 1.054e-01 4.595e-01 0.229 0.8186 Condition_FODsC:nativelang_FODsDanish 3.185e-01 4.647e-01 0.685 0.4931 Condition_FODsD:nativelang_FODsDanish 1.054e-01 4.595e-01 0.229 0.8186 Condition_FODsA:nativelang_FODsEnglish -5.390e-01 4.756e-01 -1.133 0.2571 Condition_FODsB:nativelang_FODsEnglish -3.185e-01 4.647e-01 -0.685 0.4931 Condition_FODsC:nativelang_FODsEnglish -1.178e-01 4.859e-01 -0.242 0.8085 Condition_FODsD:nativelang_FODsEnglish -5.390e-01 4.756e-01 -1.133 0.2571 Condition_FODsA:nativelang_FODsGerman 1.759e-01 2.659e-01 0.661 0.5083 Condition_FODsB:nativelang_FODsGerman -5.390e-01 2.746e-01 -1.963 0.0497 * Condition_FODsC:nativelang_FODsGerman -1.759e-01 2.659e-01 -0.661 0.5083 Condition_FODsD:nativelang_FODsGerman 2.559e-01 2.719e-01 0.941 0.3465 Condition_FODsA:nativelang_FODsHungarian 7.204e-17 3.244e-01 0.000 1.0000 Condition_FODsB:nativelang_FODsHungarian 3.185e-01 3.286e-01 0.969 0.3324 Condition_FODsC:nativelang_FODsHungarian 1.054e-01 3.249e-01 0.324 0.7457 Condition_FODsD:nativelang_FODsHungarian -1.054e-01 3.249e-01 -0.324 0.7457 Condition_FODsA:nativelang_FODsItalian 3.365e-01 3.381e-01 0.995 0.3196 Condition_FODsB:nativelang_FODsItalian -3.567e-01 3.485e-01 -1.024 0.3060 Condition_FODsC:nativelang_FODsItalian 1.054e-01 3.249e-01 0.324 0.7457 Condition_FODsD:nativelang_FODsItalian -1.054e-01 3.249e-01 -0.324 0.7457 Condition_FODsA:nativelang_FODsPolish 5.390e-01 4.756e-01 1.133 0.2571 Condition_FODsB:nativelang_FODsPolish -1.054e-01 4.595e-01 -0.229 0.8186 Condition_FODsC:nativelang_FODsPolish 5.390e-01 4.756e-01 1.133 0.2571 Condition_FODsD:nativelang_FODsPolish 3.185e-01 4.647e-01 0.685 0.4931 Condition_FODsA:nativelang_FODsRussian 3.185e-01 4.647e-01 0.685 0.4931 Condition_FODsB:nativelang_FODsRussian 1.054e-01 4.595e-01 0.229 0.8186 Condition_FODsC:nativelang_FODsRussian -3.185e-01 4.647e-01 -0.685 0.4931 Condition_FODsD:nativelang_FODsRussian -1.054e-01 4.595e-01 -0.229 0.8186 Condition_FODsA:nativelang_FODsTurkish 5.129e-02 8.272e-02 0.620 0.5352 Condition_FODsB:nativelang_FODsTurkish -6.145e-02 8.266e-02 -0.743 0.4572 Condition_FODsC:nativelang_FODsTurkish -8.494e-02 8.248e-02 -1.030 0.3031 Condition_FODsD:nativelang_FODsTurkish -3.088e-02 8.284e-02 -0.373 0.7094 Condition_FODsA:nativelang_FODsTurkish-German 5.390e-01 4.756e-01 1.133 0.2571 Condition_FODsB:nativelang_FODsTurkish-German -1.054e-01 4.595e-01 -0.229 0.8186 Condition_FODsC:nativelang_FODsTurkish-German 3.185e-01 4.647e-01 0.685 0.4931 Condition_FODsD:nativelang_FODsTurkish-German -3.185e-01 4.647e-01 -0.685 0.4931 Condition_FODsA:nativelang_FODsUkrainian-Russian 3.185e-01 4.647e-01 0.685 0.4931 Condition_FODsB:nativelang_FODsUkrainian-Russian -1.054e-01 4.595e-01 -0.229 0.8186 Condition_FODsC:nativelang_FODsUkrainian-Russian -7.732e-01 4.935e-01 -1.567 0.1172 Condition_FODsD:nativelang_FODsUkrainian-Russian -5.390e-01 4.756e-01 -1.133 0.2571 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 create a table out of these results please. use R code for this

p <- summary(fit4)$coefficients[,4]

r.squaredGLMM(fit4)
anova(fit4, test = "Chisq")
anova(fit4, test = "LRT")

# extract the p values, then put them in a data frame
df.p <- data.frame(
  p = p
)

# extract the coeffients, then put them in a data frame
df.coef <- data.frame(
  coef = c(summary(fit4)$coefficients[,1])
)

# extract the coeffients, then put them in a data frame
df.se <- data.frame(
  se = c(summary(fit4)$coefficients[,2])
)

# extract the coeffients, then put them in a data frame
df.z <- data.frame(
  z = c(summary(fit4)$coefficients[,3])
)

# extract the names and put them in a vector
df.names <- rownames(summary(fit4)$coefficients