I have asked people to tell me as many words as they can in one minute (fluency task) and I want to analyze the properties of the words they are saying. My dataset has a column for correct words (dependent variable) and three columns with continuous data corresponding to different properties of the correct words only (frequency, familiarity, imageability).
I would like to know if running a logistic regression is OK, provided that my dependent variable is only 1s. This is the code I used in R:
q <- glm (Words ~ Frequency + Familiarity + Imageability, data=df)
Perhaps one way around it is to make it so my dependent variable has 1s for correct responses and 0s for incorrect responses. However, the incorrect responses do not have any values for frequency, familiarity, etc.
I would like to know if participants said words that were higher in frequency, as opposed to familiarity or imageability. Should I then run a glmer?